Abstract
Background
While remote work brings flexibility to work life, it can also bring loneliness, emotion regulation difficulties, and some mental health symptoms. This study examined the relationship between loneliness and emotion regulation difficulties and levels of depression, anxiety, and stress in remote workers and the role of some sociodemographic variables in these relationships.
Methods
An analytical cross-sectional observational study was conducted. One hundred twenty-one participants (53.7% female, 46.3% male), aged 23–56 and working remotely for at least six months, were reached through snowball sampling and evaluated using online survey forms. Data were collected using a sociodemographic information form, the UCLA Loneliness Scale, the Depression Anxiety Stress Scale, and the Difficulties in Emotion Regulation Scale. In addition to correlation analyses and group comparisons, mediation analyses were conducted using the bootstrap method.
Results
Emotion regulation difficulties and loneliness were significantly positively associated with depression, anxiety, and stress. An increase in the number of days working remotely per week increased anxiety levels, and emotion regulation difficulties mediated this effect. Loneliness had a mediating role in the relationship between emotion regulation difficulties and depression.
Conclusions
Emotion regulation difficulties and loneliness have a significant impact on symptoms of depression, anxiety, and stress in individuals working remotely. These findings support the need to strengthen emotion regulation skills and develop policies that increase social interaction to support the mental health of remote workers.
Keywords: Remote work, Emotion regulation, Loneliness, Mental health
Background
Remote work is a type of work in which employees perform their professional work away from the office environment, usually at home or in another location, utilizing various information and communication technologies [1]. In this work model, employees communicate with their colleagues, managers, or customers in a technological environment [2]. In addition, employees can work both from the office and remotely, i.e., in a hybrid way [3]. With the COVID-19 pandemic, the remote work model has emerged as a prominent trend in many sectors and has become a permanent fixture in business life. The remote work model has been accepted as an efficient and sustainable work method in various sectors [4–6].
The remote work model can affect employees’ work-life balance and social aspects. This model can lead to psychologically significant consequences, including social isolation, loneliness, difficulties in achieving a work-life balance, changes in daily routine, and psychological pressure [7]. Researchers have demonstrated that remote work can have a positive or negative impact on mental health. It has been demonstrated that remote work can enhance employees’ quality of life by mitigating work-related conflict and stress [8]. On the other hand, numerous studies have reported an increase in loneliness, social isolation, and psychological tension with the spread of remote work [9–11]. Remote work can lead to social and professional isolation, anxiety about professional success, decreased communication with colleagues, increased mental distress, and stress levels [12].
It has also been reported in the literature that the risk of anxiety and depression is higher in remote workers. This rate was found to be especially high in individuals living alone. Anxiety rates were found to be higher in men, and depression rates were found to be higher in women working remotely [13]. Additionally, individuals working from home have higher levels of anxiety, depression, and stress than those working in a hybrid or office setting [14]. It has been shown that high levels of anxiety, depression, and stress in remote workers may be associated with poor sleep quality, increased workload, difficulty concentrating on work, low physical activity, and workplace loneliness [15, 16].
Another psychosocial adverse effect that the remote work model can create in individuals is loneliness. Results from previous studies indicate that the spread of the remote work model has led to increased social isolation and loneliness [17, 18]. Loneliness is particularly high among individuals who work remotely four days or more per week [18]. A lack of social support at work has been cited as one of the primary reasons for loneliness in the remote work model. Support from coworkers and managers has been reported to reduce loneliness significantly [19]. Given the negative relationship between loneliness and psychological well-being [20], reduced social interaction and increased social isolation for remote workers may pose a significant risk to mental health. Loneliness among remote workers is associated with emotional exhaustion, stress, anxiety, depression, decreased job satisfaction, and poor work-life balance [21]. In employees with high levels of loneliness, commitment to work and motivation decrease. This situation also negatively affects behaviors beyond just doing their own tasks and contributing voluntarily to the organization (e.g., helping others, taking initiative, etc.) [22].
Another critical factor to consider for remote workers is emotion regulation. Emotion regulation is the capacity of individuals to monitor, evaluate, and modify their emotional responses [23]. The social isolation, disruptions in communication, and uncertainties that come with working remotely can make it difficult for individuals to regulate their emotions, paving the way for various mental health problems [24]. At the same time, individuals working remotely require more emotion regulation skills to cope with their workload, tolerate uncertainty, and compensate for deficiencies in social relationships [25].
Findings from previous studies suggest that there are significant positive relationships between emotion regulation difficulties, depressive symptoms, anxiety, and chronic stress [26, 27]. Anxiety is particularly associated with the inability to maintain a distraction strategy, while depression is associated with rumination and the persistence of negative emotions [28, 29]. Frequent use of maladaptive emotion regulation strategies (e.g., suppression, avoidance, rumination) increases symptoms of depression and anxiety. In contrast, the low use of adaptive strategies (e.g., reappraisal, problem-solving, acceptance) hinders the decrease in these symptoms [29, 30]. It has been reported that negative emotion regulation strategies, such as expressive suppression, are associated with anxiety levels in individuals receiving remote education during the COVID-19 process [31].
Emotion regulation skills have a strong and reciprocal relationship with loneliness. While some findings suggest that strong emotion regulation skills can reduce loneliness, others have reported that individuals with higher levels of loneliness use maladaptive emotion regulation strategies more frequently [30, 32]. Emotion regulation difficulties are a significant predictor of loneliness. Individuals experiencing loneliness tend to use more introverted and dysfunctional strategies to cope with negative emotions. These strategies can often perpetuate or increase loneliness rather than reduce it. For example, individuals who suppress their emotions or avoid social interactions to cope with loneliness may have more difficulty forming social connections [32]. When considered together, loneliness and emotion regulation difficulties may exacerbate anxiety, depression, and stress levels.
In light of these data, it is essential to comprehensively evaluate the relationship between loneliness and emotion regulation difficulties and depression, anxiety, and stress levels in remote workers. In particular, the increasing rate of remote work at the global level, combined with the fact that this work model has become permanent in the post-pandemic period, necessitates a more in-depth examination of these relationships in terms of employees’ mental health. Although the existing literature has examined the bilateral relationships of these psychosocial variables, studies conducted together, especially on samples of individuals working remotely, are limited. This study aims to reveal the effects of remote work on individuals’ loneliness and emotion regulation difficulties and to investigate how these two variables affect depression, anxiety, and stress levels. We will also examine the effects of some sociodemographic characteristics on these variables. Thus, the study aims to contribute to the literature on the impact of remote work on mental health, to help identify psychosocial risks early, and to identify areas of intervention to strengthen the psychosocial resources of employees.
Methods
Study design and data collection
This study is an analytical cross-sectional observational study. The sample consists of individuals working remotely. The sample selection was carried out using the snowball sampling method. Participants were reached through online platforms (social media, e-mail groups, etc.). A selection process based on voluntary participation was followed by providing written information about the purpose of the study. Online consent was obtained from the participants, and the data collection process was carried out through digital survey forms.
The study included 121 remote workers. The inclusion criteria were being between 18 and 65 years old, having the mental capacity to understand and respond to instructions, being willing and able to participate in the study, and working remotely for at least six months. Exclusion criteria were incomplete survey responses and working outside a remote work model.
The sociodemographic data form, the UCLA Loneliness Scale (UCLA-20), the Depression Anxiety Stress Scale (DASS-21), and the Difficulties in Emotion Regulation Scale (DERS-16) were applied to remote workers who agreed to participate in the study via online platforms.
Ethical approval was obtained from the Giresun University Training and Research Hospital Clinical Research Ethics Committee, with the number 05.03.2025/11, on March 5, 2025.
Measures
Sociodemographic data form
The researchers created this form to evaluate sociodemographic variables such as gender, age, place of residence, marital status, education status, employment status, income status, lifestyle, alcohol and cigarette use, presence of physical and psychiatric disorders, number of years working remotely, and number of days working remotely per week.
UCLA loneliness scale
The participants’ loneliness levels were assessed with the UCLA-20, developed by Russell et al. [33] and adapted to Turkish by Demir [34]. This scale is a 20-item, 4-point Likert-type self-report instrument. Higher scores on the scale indicate that the individual experiences more intense loneliness. The internal consistency of the Turkish form of the scale was found to be high, and the Cronbach alpha coefficient was reported as 0.96.
Depression anxiety stress scale
The participants’ depression, anxiety, and stress levels were assessed with the DASS-21 developed by Lovibond and Lovibond [35] and adapted to Turkish by Yılmaz et al. [36]. This self-report scale consists of 21 items, graded on a 4-point Likert-type scale. The scale consists of three sub-dimensions, each with seven items: depression, anxiety, and stress. Higher scores on the scale indicate that the relevant mental health symptoms are experienced more severely. In the internal consistency analyses of the Turkish version of the DASS-21, Cronbach’s alpha coefficients for the subscales were determined as 0.87 for depression, 0.85 for anxiety, and 0.81 for stress.
Difficulties in emotion regulation scale
The participants’ emotion regulation difficulties were assessed using the DERS-16, developed by Gratz and Roemer [37], adapted into a short form by Bjureberg et al. [38], and translated into Turkish by Yiğit and Guzey Yiğit [39]. This self-report scale consists of 16 items. The scale, which is graded as a 5-point Likert-type scale, includes five subdimensions in its Turkish form: non-acceptance, goals, impulse, strategies, and clarity. The total DERS-16 score reflects individuals’ general emotion regulation difficulties, while the subdimensions assess specific components of these difficulties. Higher scores on the scale indicate more severe emotion regulation difficulties. In the psychometric evaluation of the Turkish form, the scale’s overall internal consistency was high, and the Cronbach alpha coefficient was reported as 0.92.
Statistical analyses
Statistical analyses were performed using IBM SPSS Statistics 27 and PROCESS Macro. Categorical variables are shown with frequency and percentage distributions. Numerical variables are shown with mean, standard deviation, median, and interquartile range values. The conformity of the data to normal distribution was assessed with skewness and kurtosis values. If the skewness and kurtosis values were between − 1.5 and + 1.5, the data were considered to be normally distributed. In pairwise comparisons, when the assumption of normality was met, the independent sample t-test was used, and when the assumption of normality was not met, the Mann-Whitney U test was used. Relationships between variables that followed normal distribution were examined with Pearson correlation analysis, and relationships between variables that did not follow normal distribution were examined with Spearman correlation analysis. In addition, mediation analyses were performed using the 5000-resampling method with the bootstrap approach at a 95% confidence interval. A two-way alpha margin of error was accepted as 0.05 in all tests.
Results
The distribution of categorical sociodemographic and health-related variables is presented in Table 1. The sample was relatively balanced in terms of gender, and the vast majority of participants resided in urban areas. Notably, over 40% reported regular smoking.
Table 1.
Distribution of categorical sociodemographic and health-related variables
| n = 121 | % | ||
|---|---|---|---|
| Gender | Female | 65 | 53.7 |
| Male | 56 | 46.3 | |
| Place of residence | City center | 120 | 99.2 |
| Village-Town | 1 | 0.8 | |
| Marital status | Married | 43 | 35.5 |
| Single | 78 | 64.5 | |
| Lifestyle | With someone | 94 | 77.7 |
| Alone | 27 | 22.3 | |
| Physical illness | No | 113 | 93.4 |
| Yes | 8 | 6.6 | |
| Psychiatric disorder | No | 106 | 87.6 |
| Yes | 15 | 12.4 | |
| Regular smoking | No | 71 | 58.7 |
| Yes | 50 | 41.3 | |
| Regular alcohol use | No | 99 | 81.8 |
| Yes | 22 | 18.2 | |
| Regular substance use | No | 118 | 97.5 |
| Yes | 3 | 2.5 | |
| Regular exercising | No | 75 | 62 |
| Yes | 46 | 38 |
n: sample size
Table 2 presents descriptive statistics for continuous variables, including demographic information, remote work characteristics, and scale scores related to mental health symptoms, loneliness, and emotion regulation difficulties.
Table 2.
Descriptive statistics of continuous sociodemographic and psychosocial variables
| Mean | Standard deviation | |
|---|---|---|
| Age | 31.20 | 6.02 |
| Education (years) | 16.19 | 2.01 |
| Number of years working remotely | 3.48 | 1.52 |
| Number of days working remotely per week | 4.49 | 1.42 |
| Monthly income (times minimum wage) | 3.77 | 2.18 |
| DASS-21 Depression | 7.26 | 4.64 |
| DASS-21 Anxiety | 5.18 | 4.14 |
| DASS-21 Stress | 7.69 | 4.44 |
| UCLA-20 Loneliness | 40.83 | 9.91 |
| DERS-16 Clarity | 4.32 | 1.70 |
| DERS-16 Goals | 8.25 | 3.48 |
| DERS-16 Impulse | 5.76 | 3.30 |
| DERS-16 Strategies | 10.49 | 5.10 |
| DERS-16 Non-acceptance | 6.29 | 3.13 |
| DERS-16 total | 35.11 | 14.63 |
DASS-21 Depression Anxiety Stress Scale, UCLA-20 UCLA Loneliness Scale, DERS-16: Difficulties in Emotion Regulation Scale
In pairwise comparisons, no statistically significant difference existed in DASS-21, UCLA-20, and DERS-16 variables except for regular cigarette use. Psychosocial scale scores were higher in smokers than in non-smokers; DASS-21 depression (t = −2.563, p = 0.012), DASS-21 anxiety (Z = −2.842, p = 0.004), DASS-21 stress (t = −2.361, p = 0.020), DERS-16 strategies (t = −2.192, p = 0.031), DERS-16 non-acceptance (t = −2.316, p = 0.023), DERS-16 impulse (t = −2.272, p = 0.026), DERS-16 total (t = −2.272, p = 0.026).
Table 3 compares whether there are significant differences in terms of mental health symptoms (depression, anxiety, stress), loneliness, and emotion regulation difficulties between individuals working remotely full-time (n = 73) and individuals working in a hybrid model (n = 48). Anxiety levels and some emotion regulation difficulties were significantly higher among full-time remote workers than hybrid workers.
Table 3.
Comparison of full-time and hybrid employees concerning mental health symptoms, loneliness, and emotion regulation difficulties variables
| Full time (n = 73) | Hybrid (n = 48) | Statistics | p | |
|---|---|---|---|---|
| Mean ± SD/Median (Q1-Q3) | ||||
| DASS-21 Depression | 7.58 ± 4.74 | 6.79 ± 4.91 | t = 0.909 | 0.365 |
| DASS-21 Anxiety | 5 (3–8) | 3.5 (1–6) | Z = −2.185 | 0.029 |
| DASS-21 Stress | 7.99 ± 4.34 | 7.23 ± 4.60 | t = 0.917 | 0.361 |
| UCLA-20 Loneliness | 42.08 ± 10.09 | 38.94 ± 9.41 | t = 1.722 | 0.088 |
| DERS-16 Clarity | 4 (3–5) | 4 (3–5) | Z = −0.071 | 0.944 |
| DERS-16 Goals | 8.67 ± 3.58 | 7.60 ± 3.25 | t = 1.664 | 0.099 |
| DERS-16 Impulse | 6.36 ± 3.61 | 4.85 ± 2.55 | t = 2.679 | 0.008 |
| DERS-16 Strategies | 11.33 ± 5.48 | 9.21 ± 4.19 | t = 2.278 | 0.025 |
| DERS-16 Non-acceptance | 6.67 ± 3.47 | 5.71 ± 2.43 | t = 1.793 | 0.075 |
| DERS-16 total | 37.37 ± 15.66 | 31.67 ± 12.27 | t = 2.129 | 0.035 |
DASS-21 Depression Anxiety Stress Scale, UCLA-20 UCLA Loneliness Scale, DERS-16 Difficulties in Emotion Regulation Scale
SD Standard deviation, Q1 First quartile, Q3 Third quartile
Table 4 presents the correlation coefficients between emotion regulation difficulties, loneliness, mental health symptoms, and the number of days working remotely. Significant positive correlations were found between DERS-16 scores and all subscales of the DASS-21. Similarly, loneliness scores showed significant positive correlations with mental health symptoms and emotion regulation difficulties. Notably, the number of days working remotely per week was positively correlated with anxiety and the impulse subdimension of the DERS-16.
Table 4.
Correlation coefficients of numerical variables in the sample
| DERS-16 total | DERS-16 Non-acceptance | DERS-16 Strategies | DERS-16 Impulse | DERS-16 Goals | DERS-16 Clarity | UCLA-20 Loneliness | DASS-21 Stress | DASS-21 Anxiety | |
|---|---|---|---|---|---|---|---|---|---|
| Number of days working remotely per week | 0.222* | 0.193* | 0.219* | 0.301* | 0.319** | ||||
| DASS-21 Depression | 0.662** | 0.413** | 0.680** | 0.490** | 0.489** | 0.451** | 0.557** | 0.713** | 0.561** |
| DASS-21 Anxiety | 0.565** | 0.439** | 0.557** | 0.522** | 0.438** | 0.409** | 0.343** | 0.752** | |
| DASS-21 Stress | 0.618** | 0.459** | 0.610** | 0.549** | 0.521** | 0.435** | 0.428** | ||
| UCLA-20 Loneliness | 0.509** | 0.331** | 0.567** | 0.464** | 0.380** | 0.373** |
DASS-21 Depression Anxiety Stress Scale, UCLA-20 UCLA Loneliness Scale, DERS-16 Difficulties in Emotion Regulation Scale
* p < 0.05
** p < 0.01
The model illustrating the mediating effect of emotion regulation difficulties on the relationship between the number of days working remotely per week and anxiety level is visualized in Fig. 1. The model was statistically significant (p < 0.001) and explained approximately 35% of the effect on anxiety level (R² = 0.345). The total effect (b = 0.858, p = 0.002) and direct effect (b = 0.492, p = 0.035) of the number of days working remotely per week on the anxiety level were statistically significant. According to the model, a one-unit increase in the number of days working remotely per week directly causes a 0.492-unit increase in anxiety level. In addition, the indirect effect of the number of days working remotely per week on anxiety level, mediated by emotion regulation difficulties, was found to be statistically significant (b = 0.366, 95% CI = 0.087–0.713). This mediation effect remained significant when the smoking variable was statistically controlled (95% CI = 0.062–0.651). As a result, it was determined that the number of days working remotely per week had a mediating role in the effect of emotion regulation difficulties on anxiety levels. The full standardized effect size value (K²) of this mediating effect was 0.124, which can be said to indicate a medium-level effect.
Fig. 1.
Mediation model of the relationship between the number of days working remotely and anxiety. Direct effect: b: 0.492, p: 0.035. Indirect effect: b: 0.366, 95% CI: 0.087–0.713. b: Unstandardized beta coefficient, p: Significance level
The models created to show the mediating effect of loneliness level on the relationship between emotion regulation difficulties and depression, anxiety, and stress levels are visualized in Fig. 2. The models are statistically significant (p < 0.001). According to the mediation analysis results, no mediating role of loneliness in the relationship between emotion regulation difficulties and anxiety and stress levels was determined (95% CI −0.016–0.044; −0.013-0.056, respectively). The total effect of emotion regulation difficulties on depression level (b = 0.186, p < 0.001), its direct effect (b = 0.130, p < 0.001), and its indirect effect through loneliness level (b = 0.056, 95% CI = 0.025–0.093) were found to be statistically significant. This mediation effect remained significant when the smoking variable was statistically controlled (95% CI = 0.026–0.093). In other words, loneliness was found to mediate the relationship between emotion regulation difficulties and depression.
Fig. 2.
Mediation model of the relationship between emotion regulation difficulties and DASS-21 dimensions. b: Unstandardized beta coefficient, p: Significance level
Discussion
This study examined the effects of emotion regulation difficulties and loneliness on depression, anxiety, and stress levels in remote workers. The findings show that emotion regulation difficulties in remote workers are closely related to higher levels of depression, anxiety, and stress, independent of loneliness. Loneliness also exhibited positive relationships with all DASS-21 subscales and had a significant mediating effect on the relationship between emotion regulation difficulties and depression. Additionally, increased weekly remote work hours were found to be a risk factor for increased anxiety levels, with some of this effect occurring through emotion regulation difficulties. In addition, some lifestyle factors, such as regular smoking, were found to be associated with emotion regulation difficulties and higher levels of depression, anxiety, and stress.
The relationship we found between emotion regulation difficulties and mental health symptom levels has been frequently identified in the literature before. It has been stated that emotion regulation difficulties function as a transdiagnostic phenomenon in the context of mental health symptoms [30, 40]. Negative emotion regulation strategies that are not solution-focused may contribute to the intensification of negative emotions and lead to the development of maladaptive coping strategies. As a result, symptoms of anxiety and depression may become more severe. Although the relationship between emotion regulation difficulties and mental health symptoms is well known, studies conducted with individuals working remotely in this context have found little space in the literature. Increased levels of depression, anxiety, and stress are linked to emotion regulation difficulties, suggesting that individuals who work from home for many days experience additional psychological strain when having to cope with workload and uncertainty alone. These findings indicate that personal coping skills may shape the relationship between remote work and mental health.
Our finding that symptoms of depression, anxiety, and stress increase when loneliness increases is consistent with previous studies demonstrating the adverse effects of workplace loneliness on mental health in remote workers [15]. Loneliness in remote work is shaped not only by physical isolation but also by multi-layered mechanisms such as energy depletion, role conflicts, and reduced social relationships [17]. In addition, there is a significant relationship between loneliness and emotion regulation difficulties. Individuals experiencing loneliness often use more maladaptive emotion regulation strategies. One study reported that emotion regulation difficulties explained approximately half of the variance in loneliness [32]. As with other study results, our findings revealed a positive correlation between emotion regulation difficulties and loneliness among remote workers. One factor affecting the mental health of remote workers is the number of days they work remotely. As the number of days they work remotely increases, their mental well-being may decrease [18, 41]. However, studies examining the relationship between remote work time and depression, anxiety, and stress are limited. We found that the number of days working remotely was positively correlated with anxiety level and emotion regulation difficulties sub-dimensions, such as impulse, strategy, and non-acceptance. Considering that remote work may be a risk factor for the deterioration of mental well-being, it seems logical that the increase in remote work time is correlated with the increase in anxiety levels. Individual characteristics or emotion regulation difficulties that may arise from working remotely, such as difficulty controlling impulsive behaviors, feeling unable to achieve effective strategies to manage negative emotions, denying the negative emotions they experience, or blaming themselves for these emotions, may explain the increase in anxiety levels. Additionally, remote workers may lack these skills because they implement emotion regulation strategies through a digital environment [42]. In line with these findings, we found that anxiety levels and emotion regulation difficulties scores were lower in individuals working in the hybrid model compared to individuals working full-time remotely. Our findings suggest that part of this anxiety-related impact may be mediated by the emotion regulation difficulties inherent in remote work. That is, increased anxiety levels in those who work from home for large numbers of days appear to be related in part to the difficulties these individuals have in managing their emotions. To our knowledge, this is a novel finding in the literature, as previous studies have not explained the relationship between the number of days working remotely and anxiety through emotion regulation difficulties. However, considering the direct effect of the number of days working remotely on the anxiety level, it can be said that emotion regulation difficulties cannot entirely explain this relationship. Other factors related to this relationship should be examined in further studies.
Depression, anxiety, stress, and emotion regulation difficulties scores were significantly higher in individuals with smoking habits. Smoking is common among remote workers. This condition is associated with easier access to smoking, reduced social support, and dysfunctional coping strategies [43]. There is a bidirectional positive relationship between mental health symptoms and smoking in terms of biological and psychosocial mechanisms [44]. In addition, smoking is closely related to emotion regulation difficulties [45]. This may be related to the fact that stressed and anxious individuals often prefer smoking as a coping mechanism. However, more research is needed before a causal interpretation can be made, especially regarding remote workers.
The relationships between loneliness, emotion regulation difficulties, and symptoms such as depression and anxiety are complex. In the mediation model we created to clarify this complexity, we found that loneliness has a mediating role in the effect of emotion regulation difficulties on depression. In other words, some of the depressive symptoms that increase with emotion regulation difficulties can be explained by the loneliness that individuals experience. According to the model we created, emotion regulation difficulties may cause loneliness, and loneliness may cause depressive symptoms. As loneliness increases, people may have more difficulty coping with their negative emotions and develop depressive symptoms. However, this finding should be interpreted cautiously due to the study’s cross-sectional design. Nevertheless, this result provides an original contribution to the literature. This mediating relationship offers a holistic perspective on how emotional and social factors can interact to impact mental health in a remote work environment. In addition, the findings show that emotion regulation difficulties are closely related to high levels of depression, anxiety, and stress, regardless of the loneliness. In other words, remote workers experiencing emotion regulation difficulties reported higher levels of depressive symptoms, anxiety, and stress, even if they did not experience loneliness. This finding highlights the importance of developing and enhancing emotion regulation skills for individuals working remotely.
The relationships between emotion regulation difficulties and gender [46], lifestyle [47], and exercise [48] have been previously reported. Exercise has been reported to be associated with loneliness [49]. In addition, women have been found to experience greater loneliness as a result of social isolation [50], and those without a romantic relationship or living alone also experience greater loneliness [33, 51]. However, we did not find any significant effects of social variables such as gender, marital status, lifestyle, and exercise on emotion regulation difficulties and loneliness. Studies on these variables in individuals working remotely are limited in the literature, and our results may represent a different group from the general population. Contrary to existing literature, we did not find any significant effects of gender, marital status, lifestyle, and exercise on depression, anxiety, or stress levels in remote workers [13, 15, 52]. Similarly, we found no significant relationship between remote work and loneliness or between full-time work and depression, stress, and loneliness. Additionally, loneliness did not mediate the relationship between emotion regulation difficulties and anxiety and stress. These contradictory findings suggest that the effects of remote work may vary depending on context and individual circumstances. Many factors not assessed in our study (e.g., social support, working conditions, self-discipline) may modify the effects of remote work on mental health. Therefore, the discrepancy between the results reported in the literature and our findings suggests that the nature of the remote work experience and the employees’ personal/organizational resources may vary. The small sample size may have prevented some results from reaching significance. Additionally, the fact that our study focused more on risk factors and the sample characteristics (mostly full-time remote workers) may have highlighted the adverse effects of remote work more clearly.
The findings offer some theoretical and practical implications. In the context of remote work, the role of emotion regulation and the need for social togetherness in mental health is confirmed in line with the literature [53, 54]. Attachment and social needs theories predict that when individuals’ needs for belonging and support are unmet (for example, when they experience loneliness), their psychological well-being will be damaged [55]. Additionally, individuals experience psychological distress when their stress-coping and emotion-regulation skills are inadequate [56]. The findings indicate that individuals who face social isolation in a remote work environment are more likely to have mental health problems if their emotion regulation skills are weak. This result highlights that, in addition to the freedom and flexibility that remote work brings, employees’ needs for building relationships and managing emotions are equally important. From a practical perspective, our findings suggest the need for targeted interventions at both individual and organizational levels to protect mental health in remote work environments. In particular, supporting employees’ emotion regulation skills and increasing their opportunities for social interaction can play a critical role in reducing levels of depression, anxiety, and stress. The physical separation of remote workers can often lead to emotional and social needs not being fully met despite the use of communication technologies. Therefore, it is essential to provide training and resources that enable employees to manage their emotions in a healthy manner, as well as to develop practices that reinforce a sense of belonging in the workplace. As remote work becomes more widespread, employers should develop supportive policies that address the psychosocial needs of employees. Mental health professionals can support employees’ mental well-being by offering specific intervention programs that address loneliness and emotion regulation difficulties. Policymakers should create regulations that encourage employers to protect the mental health of their employees and raise public awareness through awareness campaigns. Thus, the mental health of individuals can be protected more effectively in remote work conditions. In conclusion, the interactions revealed by our research demonstrate that the development and strengthening of emotional skills, as well as social ties, are essential for enhancing psychological resilience among remote workers.
Limitations and future directions
This study has several limitations. First, the cross-sectional design prevents any conclusions about causality. Second, the reliance on self-report measures may have introduced bias due to social desirability or common method variance. Third, the sample was relatively small and demographically homogeneous (e.g., predominantly urban and educated), which may limit the generalizability of the findings. Additionally, considering that some participants transitioned to a hybrid model or had varying lengths of remote work experience, it became challenging to determine the impact of variables such as the number of years of remote work experience. Lastly, objective assessments such as clinical interviews were not included. Future studies should address these limitations with longitudinal designs, larger and more diverse samples, and multimethod approaches.
Conclusions
In today’s world, where remote work is becoming increasingly widespread, developing strategies to protect the mental well-being of employees has become critical. Our findings provide an important framework for understanding the relationship between emotion regulation difficulties, loneliness, and mental health during remote work. Based on our results, we recommend (1) supporting employees in developing emotion regulation skills through training and resources, (2) implementing organizational policies that promote social interaction and reduce workplace isolation, and (3) encouraging mental health professionals to develop targeted interventions for remote workers. Further longitudinal research is needed to understand better the directionality and long-term consequences of these psychosocial dynamics.
Acknowledgements
Not applicable.
Abbreviations
- DASS-21
Depression Anxiety Stress Scale
- UCLA-20
UCLA Loneliness Scale
- DERS-16
Difficulties in Emotion Regulation Scale
- SPSS
Statistical Package for the Social Sciences
- CI
Confidence interval
- SD
Standard deviation
- Q1/Q3
First quartile / third quartile
- b
Unstandardized beta coefficient
- R²
Coefficient of determination (explained variance)
- K²
Standardized effect size in mediation analysis
- p
p-value (statistical significance level)
- Z
Z-score (used in non-parametric tests)
- t
t-value (used in t-tests)
Authors’ contributions
Conceptualization, U.K., Ö.F.Ş. and M.H.Ş.; methodology, U.K., Ö.F.Ş. and M.H.Ş.; software, U.K.; validation, U.K. and M.H.Ş.; formal analysis, U.K., Ö.F.Ş. and M.H.Ş.; investigation, U.K., Ö.F.Ş. and M.H.Ş.; resources, U.K. and M.H.Ş.; data curation, U.K., Ö.F.Ş. and M.H.Ş.; writing—original draft preparation, U.K.; writing—review and editing, M.H.Ş. and Ö.F.Ş.; visualization, U.K.; supervision, M.H.Ş. and Ö.F.Ş. All authors approved the final version of the manuscript.
Funding
There is no funding associated with the study.
Data availability
The datasets used during the current study are available from the corresponding author on reasonable request.
Declarations
Ethics approval and consent to participate
The Giresun Training and Research Hospital Clinical Research Ethics Committee approved the research, decision number 05.03.2025/11. The research was conducted in accordance with the Declaration of Helsinki. All participants provided informed consent before participating in the study.
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
- 1.Felstead A. Remote working: A research overview. Routledge; 2022. 10.4324/9781003247050.
- 2.Leonardi PM, Parker SH, Shen R. How remote work changes the world of work. Annu Rev Organ Psychol Organ Behav. 2024;11(1):193–219. 10.1146/annurev-orgpsych-091922-015852. [Google Scholar]
- 3.Vartiainen M. Telework and remote work. Oxf Res Encycl Psychol. 2021. 10.1093/acrefore/9780190236557.013.850. [Google Scholar]
- 4.Sytsma T. The Globalization of Remote Work: Will Digital Offshoring Make Waves in the US Labor Market? 2022. 10.7249/pea1141-7
- 5.Leonardi PM. COVID-19 and the new technologies of organizing: digital exhaust, digital footprints, and artificial intelligence in the wake of remote work. J Manage Stud. 2020;58(1):249. 10.1111/joms.12648. [Google Scholar]
- 6.Gifford J. Remote working: unprecedented increase and a developing research agenda. Taylor & Francis; 2022. pp. 105–13. 10.1080/13678868.2022.2049108.
- 7.Pullokaran L, Joseph P. Working remotely: employees benefits and challenges. Int J Eng Technol Manage Sci. 2023;7(1):34–. 10.46647/ijetms.2023.v07i01.007. 7. [Google Scholar]
- 8.Rodrigues EF, Lemos MF. Repercussions of home office on the mental health of teleworkers: integrative review: repercussões do home office Na Saúde mental de teletrabalhadores: Revisão integrativa. Concilium. 2024;24(12):144–65. 10.53660/clm-3637-24m11. [Google Scholar]
- 9.Sim J, Yun B, Park H, Oh J, Yoon J. Rising mental health issues from remote work challenges in South Korea amid COVID-19. Eur J Pub Health. 2024;34(Supplement3):ckae144. 10.1093/eurpub/ckae144.2208. [Google Scholar]
- 10.Van Zoonen W, Sivunen AE. The impact of remote work and mediated communication frequency on isolation and psychological distress. Eur J Work Organ Psychol. 2022;31(4):610–21. 10.1080/1359432X.2021.2002299. [Google Scholar]
- 11.Nowrouzi-Kia B, Haritos AM, Long B-ZS, Atikian C, Fiorini LA, Gohar B, et al. Remote work transition amidst COVID-19: impacts on presenteeism, absenteeism, and worker well-being—a scoping review. PLoS One. 2024;19(7): e0307087. 10.1371/journal.pone.0307087. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Yacub A, Drysdale MT, Callaghan SA. Challenges of remote working, perceived peer support, mental health and well-being of WIL students. Educ Train. 2024;66(9):1165–82. 10.1108/ET-02-2023-0060. [Google Scholar]
- 13.Moran MR, Heller O, Chun Y, Shlomo Y, Grinstein-Weiss M. Examining associations between remote work and anxiety and depression: a longitudinal survey study in Israel. BMJ Public Health. 2023. 10.1136/bmjph-2023-000133. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Juraś-Darowny M, Król M, Chodkiewicz J, Talarowska M. The level of depression, anxiety and job satisfaction among young contact centre employees during the COVID-19 pandemic. Archives Psychiatry Psychother. 2023;25(4). 10.12740/APP/169192.
- 15.Şentürk E, Sağaltıcı E, Geniş B, Günday Toker Ö. Predictors of depression, anxiety and stress among remote workers during the COVID-19 pandemic. Work. 2021;70(1):41–51. 10.3233/WOR-210082. [DOI] [PubMed] [Google Scholar]
- 16.Dávila Morán RC. Influence of remote work on the work stress of workers in the context of the COVID-19 pandemic: a systematic review. Sustainability. 2023;15(16):12489. 10.3390/su151612489. [Google Scholar]
- 17.Walz T, Kensbock JM, De Jong SB, Kunze F. Lonely@ work@ home?? The impact of work/home demands and support on workplace loneliness during remote work. Eur Manag J. 2024;42(5):767–78. 10.1016/j.emj.2023.05.001. [Google Scholar]
- 18.Miyake F, Odgerel C-O, Hino A, Ikegami K, Nagata T, Tateishi S, et al. Job stress and loneliness among desk workers during the COVID-19 pandemic in Japan: focus on remote working. Environ Health Prev Med. 2022;27:33. 10.1265/ehpm.22-00107. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Wax A, Deutsch C, Lindner C, Lindner SJ, Hopmeyer A. Workplace loneliness: the benefits and detriments of working from home. Front Public Health. 2022;10–2022. 10.3389/fpubh.2022.903975. [DOI] [PMC free article] [PubMed]
- 20.Çiçek İ. Mediating role of self-esteem in the association between loneliness and psychological and subjective well-being in university students. International Journal of Contemporary Educational Research. 2021;8(2):83–97. 10.33200/ijcer.817660
- 21.Becker WJ, Belkin LY, Tuskey SE, Conroy SA. Surviving remotely: how job control and loneliness during a forced shift to remote work impacted employee work behaviors and well-being. Hum Resour Manage. 2022;61(4):449–64. 10.1002/hrm.22102. [Google Scholar]
- 22.Bareket-Bojmel L, Chernyak-Hai L, Margalit M. Out of sight but not out of mind: the role of loneliness and hope in remote work and in job engagement. Pers Individ Differ. 2023;202: 111955. 10.1016/j.paid.2022.111955. [Google Scholar]
- 23.McRae K, Gross JJ. Emotion regulation. Emotion. 2020;20(1):1–9. 10.1037/emo0000703. [DOI] [PubMed] [Google Scholar]
- 24.Minusa S, Yoshimura C, Mizuno H. Emodiversity evaluation of remote workers through health monitoring based on intra-day emotion sampling. Front Public Health. 2023;11:1196539. 10.3389/fpubh.2023.1196539. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Audrin B, Audrin C, Fernandez S, Terrier L. Out of sight, out of mind? Investigating the impact of emotional intelligence on counterproductive work behavior in remote work. J Manage Dev. 2025;44(1):83–95. 10.1108/JMD-02-2024-0049. [Google Scholar]
- 26.Boudriga S, Lagha M, Methni M, Youssef YB, Romdhane IB, Homri W, et al. Assessing the relationships between emotion regulation, depression, anxiety, and stress symptoms in a Tunisian university setting. Eur Psychiatry. 2024;67(S1):S536–S536. 10.1192/j.eurpsy.2024.1113. [Google Scholar]
- 27.Honan I, Waight E, Bratel J, Given F, Badawi N, McIntyre S, et al. Emotion regulation is associated with anxiety, depression and stress in adults with cerebral palsy. J Clin Med. 2023;12(7):2527. 10.3390/jcm12072527. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Wu C, Tan Y, Blain SD, Shao S, Jia L, Wang X. Emotion regulation difficulties in depression and anxiety: evidence from the dynamics of strategy use and daily affect. J Context Behav Sci. 2024;33: 100781. 10.1016/j.jcbs.2024.100781. [Google Scholar]
- 29.Dryman MT, Heimberg RG. Emotion regulation in social anxiety and depression: a systematic review of expressive suppression and cognitive reappraisal. Clin Psychol Rev. 2018;65:17–42. 10.1016/j.cpr.2018.07.004. [DOI] [PubMed] [Google Scholar]
- 30.Schäfer JÖ, Naumann E, Holmes EA, Tuschen-Caffier B, Samson AC. Emotion regulation strategies in depressive and anxiety symptoms in youth: a meta-analytic review. J Youth Adolesc. 2017;46(2):261–76. 10.1007/s10964-016-0585-0. [DOI] [PubMed] [Google Scholar]
- 31.Zhao T, Fu Z, Lian X, Ye L, Huang W. Exploring emotion regulation and perceived control as antecedents of anxiety and its consequences during Covid-19 full remote learning. Front Psychol. 2021;12:675910. 10.3389/fpsyg.2021.675910. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Preece DA, Goldenberg A, Becerra R, Boyes M, Hasking P, Gross JJ. Loneliness and emotion regulation. Pers Indiv Differ. 2021;180: 110974. 10.1016/j.paid.2021.110974. [Google Scholar]
- 33.Russell D, Peplau LA, Cutrona CE. The revised UCLA loneliness scale: concurrent and discriminant validity evidence. J Pers Soc Psychol. 1980;39(3):472. 10.1037/0022-3514.39.3.472. [DOI] [PubMed] [Google Scholar]
- 34.Demir AG. UCLA yalnızlık ölçeğinin geçerlik ve güvenirliği. Psikoloji Dergisi. 1989;7(23):14–8.
- 35.Lovibond PF, Lovibond SH. The structure of negative emotional states: comparison of the depression anxiety stress scales (DASS) with the Beck depression and anxiety inventories. Behav Res Ther. 1995;33(3):335–43. 10.1016/0005-7967(94)00075-U. [DOI] [PubMed] [Google Scholar]
- 36.Yılmaz Ö, Boz H, Arslan A. The validity and reliability of depression stress and anxiety scale (DASS21) Turkish short form. Res Financial Economic Social Stud. 2017;2(2):78–91. [Google Scholar]
- 37.Gratz KL, Roemer L. Multidimensional assessment of emotion regulation and dysregulation: development, factor structure, and initial validation of the difficulties in emotion regulation scale. J Psychopathol Behav Assess. 2004;26:41–54. 10.1023/B:JOBA.0000007455.08539.94. [Google Scholar]
- 38.Bjureberg J, Ljótsson B, Tull MT, Hedman E, Sahlin H, Lundh L-G, et al. Development and validation of a brief version of the difficulties in emotion regulation scale: the DERS-16. J Psychopathol Behav Assess. 2016;38:284–96. 10.1007/s10862-015-9514-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Yiğit İ, Guzey Yiğit M. Psychometric properties of Turkish version of difficulties in emotion regulation scale-brief form (DERS-16). Curr Psychol. 2019;38:1503–11. 10.1007/s12144-017-9712-7. [Google Scholar]
- 40.D’Avanzato C, Joormann J, Siemer M, Gotlib IH. Emotion regulation in depression and anxiety: examining diagnostic specificity and stability of strategy use. Cogn Therapy Res. 2013;37:968–80. 10.1007/s10608-013-9537-0. [Google Scholar]
- 41.Shimura A, Yokoi K, Ishibashi Y, Akatsuka Y, Inoue T. Remote work decreases psychological and physical stress responses, but full-remote work increases presenteeism. Front Psychol. 2021;12:730969. 10.3389/fpsyg.2021.730969. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Wadley G, Smith W, Koval P, Gross JJ. Digital emotion regulation. Curr Dir Psychol Sci. 2020;29(4):412–8. 10.1177/0963721420920592. [Google Scholar]
- 43.Sonoda K, Okawa S, Tabuchi T. Association of remote work with tobacco and alcohol use: a cross-sectional study in Japan. BMC Public Health. 2025;25(1):103. 10.1186/s12889-024-21066-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Park SK, Oh C-M, Kim E, Ryoo J-H, Jung JY. The longitudinal analysis for the association between smoking and the risk of depressive symptoms. BMC Psychiatry. 2024;24(1):364. 10.1186/s12888-024-05828-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Schadegg MJ, Dixon LJ, Lee AA. Emotion regulation difficulties and smoking behavior among adults with chronic obstructive pulmonary diseases. Psychiatr Q. 2024;95(3):433–45. 10.1007/s11126-024-10080-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Wu L, Zhou R. Effectiveness of acute aerobic exercise in regulating emotions in individuals with test anxiety. Biol Psychol. 2024;193: 108873. 10.1016/j.biopsycho.2024.108873. [DOI] [PubMed] [Google Scholar]
- 47.Eldesouky L, Goldenberg A, Ellis K. Loneliness and emotion regulation in daily life. Pers Individ Differ. 2024;221: 112566. 10.1016/j.paid.2024.112566. [Google Scholar]
- 48.Liu J, Gao S, Zhang L. Effects of physical exercises on emotion regulation: a meta-analysis. Medrxiv. 2022:2022.07. 04.22277120. 10.1101/2022.07.04.22277120
- 49.Ahn J, Falk EB, Kang Y. Relationships between physical activity and loneliness: a systematic review of intervention studies. Curr Res Behav Sci. 2024;6: 100141. 10.1016/j.crbeha.2023.100141. [Google Scholar]
- 50.Lepinteur A, Clark AE, Ferrer-i-Carbonell A, Piper A, Schröder C, d’Ambrosio C. Gender, loneliness and happiness during COVID-19. J Behav Experimental Econ. 2022;101:101952. 10.1016/j.socec.2022.101952. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 51.Mansfield R, Di Gessa G, Patel K, McElroy E, Wels J, Henderson M, et al. Examining the interrelationships between social isolation and loneliness and their correlates among older British adults before and during the COVID-19 lockdown: evidence from four British longitudinal studies. Innov Aging. 2024;8(1):igad126. 10.1093/geroni/igad126. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 52.Matthews TA, Chen L, Omidakhsh N, Zhang D, Han X, Chen Z, et al. Gender difference in working from home and psychological distress-a national survey of US employees during the COVID-19 pandemic. Ind Health. 2022;60(4):334–44. 10.2486/indhealth.2022-0077. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 53.Muñoz-Martínez AM, Naismith I. Social connectedness, emotional regulation, and health behaviors as correlates of distress during lockdown for COVID‐19: A diary study. Appl Psychology: Health Well‐Being. 2023;15(2):536–60. 10.1111/aphw.12395. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 54.Marroquín B, De Rutte J, May CL, Wisco BE. Emotion regulation in context: social connectedness moderates concurrent and prospective associations with depressive symptoms. J Soc Clin Psychol. 2019;38(7):605–26. 10.1521/jscp.2019.38.7.605. [Google Scholar]
- 55.Bowlby J. Attachment and Loss. Vol. 1: Attachment. New York: Random House; 1969.
- 56.Gross JJ. The emerging field of emotion regulation: an integrative review. Rev Gen Psychol. 1998;2(3):271–99. 10.1037/1089-2680.2.3.271. [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets used during the current study are available from the corresponding author on reasonable request.