The Mediating Role of Trait Mindfulness in Academic Stress: A Cross-Sectional Study Among Italian University Students

Abstract

Background: Stress is a significant factor influencing the mental well-being of students, and mindfulness strategies have been associated with reduced academic stress. Nevertheless, there is a limited body of research investigating stress and trait mindfulness in a sample of Italian university students. This study aims to explore the relationship between academic stress, effort-reward imbalance, and trait mindfulness. Methods: Perceived stress, effort-reward imbalance, and trait mindfulness in 442 Italian university students (mean age = 23.37 ± 4.33) were assessed through the Perceived Stress Scale (PSS), Effort-Reward Imbalance – Student Questionnaire (ERI-SQ) and Five Facet Mindfulness Questionnaire (FFMQ). Results: Pearson correlation analysis showed that PSS negatively correlates with FFMQ and it positively correlates with ERI-SQ, while FFMQ negatively correlates with ERI-SQ. Furthermore, mediation analysis revealed that FFMQ partially mediates the effect of ERI-SQ on PSS. Conclusions: This study provides the first examination of the relationships between perceived stress, effort-reward imbalance, and trait mindfulness among Italian students. The findings suggest that trait mindfulness is associated with lower levels of perceived stress and could potentially mediate the relationship between effort-reward imbalance and stress. These insights may inform future research and interventions aimed at reducing academic stress.

Keywords

Academic stress effort-reward imbalance mindfulness trait mindfulness mindfulness based intervention

Introduction

Academic Stress

Stress is a state of mental concern or tension caused by a challenging situation (WHO, 2023), identified as a normal human response to challenges and threats. However, our responses and coping mechanisms with stress mark significant differences in one’s well-being (WHO, 2023). In fact, stress affects mind-body changes, serving when chronic or acute as a risk factor for mental and physical impairment and diminished quality of life (APA, 2018; Selye, 1946). Increased susceptibility towards stress is registered among youths, with increased rates partially relating to the developmental challenges adolescents undergo while transitioning to adulthood (Prowse et al., 2021). During their academic path, the demands presented by college or university attendance are high, with moderate levels of perceived academic-related stress considered adaptive concerning the contextual demands (Martinez-Rubio et al., 2023; Prowse et al., 2021). Yet, overloading academic challenges constitute one of the most frequent and impairing sources of distress for young adults pursuing higher education, alongside social relationships and financial strains (Martinez-Rubio et al., 2023; Metzger et al., 2017; Prowse et al., 2021). High levels of academic stress are associated with impaired quality of life, low to scarce overall life satisfaction, college drop-out, low self-efficacy, anxiety, depression, and poor sleep quality (Barbayannis et al., 2022; Martinez-Rubio et al., 2023). Various studies have outlined the role of academic stress and burnout as impairing outcomes when an imbalance between effort and reward is registered (Hodge et al., 2020; Kim et al., 2017; Williams et al., 2017). According to the homonymous Effort-Reward Imbalance model (Siegrist, 2004), a great and persistent imbalance between one’s effort and rewards, often manifested with overcommitment to tasks, generates stress and is responsible in the long run for psychopathological outcomes (Hodge et al., 2020; Siegrist, 2004; Williams et al., 2017). Further studies have outlined how overcommitment and low reward are linked to poor physical and mental health (Hodge et al., 2020; Williams et al., 2017).

Mindfulness as a Protective Factor for Stress

An individual’s dispositional aptitude to be and act mindful is referred to as trait mindfulness, namely, a personality trait embodying the ability to pay attention and exhibit awareness of the present moment without judgment (Brown & Ryan, 2003). This personality trait is often measured with self-report questionnaires such as the Five Facet Mindfulness Questionnaire (FFMQ; Baer et al., 2006), focusing on five core aspects such as the ability to observe, describe one’s own current experience, awareness, non-judgmental and non-reactive attitude (Baer et al., 2006). Several studies outline how higher levels of dispositional mindfulness are associated with lower levels of perceived stress (Zimmaro et al., 2016) and with more adaptive coping strategies (Weinstein et al., 2009), and it can mitigate the effects of stress on anxiety and depression symptomatology (Bergin & Pakenham, 2016). Additionally, FFMQ facets are associated with lower levels of stress and mood disorder symptoms (Cash & Whittingham, 2010) in university student populations (Medvedev et al., 2018). Trait mindfulness also mediates the relationship, respectively, between perceived loneliness and stress, and resilience and academic stress (Coutts-Smith & Phillips, 2023; Liu et al., 2022; Yu et al., 2021; Zahra & Riaz, 2017). Drawing on these premises, there is an increasing need to investigate the prevalence of academic stress in the Italian University student population, whose rates of perceived stress, as well as its relationship with the Effort-Reward Imbalance model, are scarcely studied and reported, alongside the prevalence of trait mindfulness across the sample, to study its interplay with academic distress. It is noteworthy to investigate the role of trait mindfulness facets (regarding the FFMQ scale facets) as potential mediators of the relationship between perceived stress and student effort-reward imbalance. Few studies have explored such relationships in the academic realm, specifically regarding the Italian university context (Portoghese et al., 2019). Evidence is therefore needed to better understand the status of psychological well-being in the Italian academic contexts and to address potential psychopathological sequelae and protective factors, to effectively help institutions design preventative screenings and active interventions promoting well-being and adaptive stress management techniques, leveraging on the benefits of trait mindfulness and mindfulness-based interventions.

Purpose

The primary aim of this study is to estimate the levels of perceived stress in a sample of Italian university students, along with trait mindfulness and effort-reward imbalance states. Assessments were carried out respectively with the Perceived Stress Scale (PSS), Five Facet Mindfulness Questionnaire (FFMQ), and Effort-Reward Imbalance-Student Questionnaire (ERI-SQ).

The secondary aim of the study is to investigate the relationship between trait mindfulness, effort-reward imbalance, and academic stress. In light of previous evidence highlighting a) significant associations between the effort-reward imbalance model, academic stress, and risk for burnout (Hodge et al., 2020; Kim et al., 2017; Williams et al., 2017), and b) associations between levels of trait mindfulness and levels of perceived academic stress (Medvedev et al., 2018), a mediation model has been proposed, testing the association between trait mindfulness effort-reward imbalance and stress. It has been hypothesized that trait mindfulness serves as a significant mediator for the effect of effort-reward imbalance states on academic stress.

Considering such results, relationships between the variables were explored. The first hypothesis of the study entailed that: (1) prevalence rates of distress align with current literature, signaling medium to severe levels of stress in samples of university students; (2) significant associations between levels of perceived distress, trait mindfulness, and effort-reward imbalance were identified. Specifically, it has been hypothesized that higher levels of trait mindfulness are associated with lower levels of perceived distress, whereas high levels of effort-reward imbalance are associated with higher levels of perceived distress.

Methods

Study Design

A cross-sectional study was conducted by recruiting a sample of Italian students currently enrolled at Italian universities (bachelor’s degree, master’s degree, and PhD programs). Recruitment occurred via social media and snowball sampling. Participants were asked to complete an online survey administered through Google Forms from November 2023 to January 2024. The survey’s homepage included an online consent form detailing the study’s purpose, the time required for completion, and privacy policy information. To ensure participant anonymity and confidentiality, no IP addresses, email addresses, or any other personally identifiable information were collected. This means that demographic data such as age and gender cannot be traced back to individual participants. The investigators and research team did not actively advertise to increase recruitment rates. In total, 442 Italian university students agreed to participate in the survey and completed it.

Ethical Considerations

The study was approved by the Ethics Committee of Ethics Commission of Sigmund Freud University in Vienna, following the guidelines of the 1964 Helsinki Declaration and its later amendments, as well as Italian privacy laws. The ethical approval process involved a detailed review to ensure that the study posed no more than minimal risk to participants. According to the decision tree used by the Ethics Committee, additional considerations were made to confirm that participants did not belong to vulnerable groups such as minors, individuals with cognitive impairments, those under legal guardianship, or individuals experiencing severe stress or emergencies. No use of third-party software that might compromise data privacy was employed, and the study design was reviewed to ensure compliance with data protection regulations.

Participants

The sample for this research consisted of 76.4% females (n = 337) and 23.76% males (n = 105). Participants of this study ranged from 18 to 60 years of age (mean age = 23.37 ± 4.33) and were enrolled in bachelor’s degree programs (n = 210), 48.6% were enrolled in master’s degree programs (n = 215), 2.3% were enrolled in master programs (n = 10) and 1.6% were enrolled in PhD programs (n = 7). Overall, 68.6% of participants attend universities in Northern Italy (n = 303), 14.7% attend universities in the Central regions (n = 65) and 16.7% attend universities in Southern Italy and the Islands (n = 74). Out-of-town students were 38.5% (n = 170). 42.1% of the participants are actively working or engaged in work-related activities while pursuing their university studies (n = 186), while 57.1% are not working during their studies (n = 256). Concerning mindfulness practice, only 3.2% reported engaging in regular practice (n = 14), while 36.7% indicated practicing mindfulness occasionally (n = 162). Additionally, 48.6% expressed never having practiced mindfulness but expressed interest in trying it (n = 215), and 11.5% reported having neither practiced mindfulness nor having any interest in doing so (n = 51).

Measures

The self-administered questionnaire consisted of the Perceived Stress Scale (PSS - 10; Cohen, 1988; Italian version; Fossati, 2010), the Effort-Reward Imbalance - Student Questionnaire (ERI-SQ; Wege et al., 2017; Italian version; Portoghese et al., 2019) and the Five Facet Mindfulness Questionnaire (FFMQ; Baer et al., 2006; Italian version; Giovannini et al., 2014).

The internal consistency of each scale and its subscales was evaluated using Cronbach’s alpha to ensure the reliability of the measures within the study sample. The PSS demonstrated good internal consistency, with a Cronbach’s alpha of 0.87, indicating a reliable measurement of perceived stress. The ERI-SQ, while showing lower overall internal consistency (α = 0.32), exhibited varying reliability across its subscales: Effort (α = 0.77) demonstrated acceptable reliability, while Reward (α = 0.03) and Overcommitment (α = 0.36) had lower consistency, suggesting that the interpretation of items or sample-specific factors may have influenced these results. In contrast, the FFMQ showed strong internal consistency, both overall (α = 0.90) and across its subscales: Observing (α = 0.75), Describing (α = 0.90), Acting with Awareness (α = 0.88), Non-Judging (α = 0.90), and Non-Reactivity (α = 0.78), confirming its robustness as a measure of trait mindfulness in this context.

Perceived Stress Scale

The Perceived Stress Scale (PSS) is a self-report tool designed to assess psychological distress experienced in the preceding month, as initially introduced by Cohen (1983). Originally, the scale comprised 14 items (Cohen et al., 1983) but was subsequently condensed to a 10-item version (Cohen, 1988). For this study, the 10-item variant was used. The total score is derived from the summation of responses to 6 positive stress predictors, rated on a 5-point Likert scale (ranging from 0 to 4), and 4 negative predictors, evaluated on a reversed 5-point Likert scale (Cohen, 1988). A higher score indicates a heightened probability of perceived stress. To interpret PSS scores, a categorization was established: scores between 0 and 13 are categorized as low stress, scores ranging from 14 to 26 are indicative of moderate stress, and scores falling within the range of 27–40 are considered indicative of high perceived stress (State of New Hampshire Employee Assistance Program, nd).

Effort-Reward Imbalance - Student Questionnaire

The Effort-Reward Imbalance Student Questionnaire (ERI-SQ) was employed to assess stress related to academic pursuits in university students and comprises 12 items distributed across three subscales: effort (two items), reward (five items), and overcommitment (five items). Historically, this instrument has been extensively used in the examination of work-related stress and its health implications among employed individuals (Siegrist, 1996; van Vegchel et al., 2005). Responses to all items are recorded on a 4-point rating scale, ranging from 1 (strongly disagree) to 4 (strongly agree). Effort, reward, and overcommitment scores are determined as the sum of the respective items. Following the reversal of reverse-scored items, the Effort-Reward Imbalance (ERI) score is computed using the formula: ERI = (effort score)/[(reward score)*(correction factor)] with a correction factor of 0.4, accounting for the disparate number of items for effort (n = 2) and reward (n = 5) (Siegrist et al., 2004). A higher composite score indicates elevated levels of effort, reward, over-commitment, and effort-reward imbalance.

Five Facet Mindfulness Questionnaire

The 39-item Five-Facet Mindfulness Questionnaire (FFMQ) is a self-report measure i.e. based on a five-facet model (i.e., Observe, Describe, Act with Awareness, Nonjudge, and Non-react). All the items are assessed on a 5-point Likert scale, ranging from 1 (never or very rarely true) to 5 (very often or always true). Following the reversal of reverse-scored items, the total score can be computed by summing the scores for each item, where higher total scores indicate a heightened degree of mindfulness (total score ranging from 39 to 195). This instrument was employed to investigate trait mindfulness, defined as the innate capacity to pay and sustain attention to present-moment experiences with an open and nonjudgmental attitude (Brown & Ryan, 2003).

Statistical Analyses

The program used to perform statistical analysis were R version 4.4.1 (R Core Team, 2024) and RStudio version 2024.04.2 + 764 (Posit Team, 2024), with packages lavaan (Rosseel, 2012) and psych (Revelle, 2024).

Descriptive Statistics

Preliminary descriptive statistics were computed aiming at describing the recruited sample.

Preliminary Analyses

Assumptions for the general linear model were tested before performing parametric analyses. To assess the differences between groups in PSS, ERI-SQ, and FFMQ scores, Welch’s t-tests and one-way between ANOVA analyses were conducted. To examine the presence of possible relationships between age, PSS, ERI-SQ, FFMQ, and its subscales, Pearson correlation analyses were conducted.

Mediation Analysis

A mediation model with multiple mediators was tested to analyze whether FFMQ facets mediate the relationship between ERI-SQ subscales and perceived stress. We hypothesized that the relationship between the ERI-SQ subscales (effort, reward, and overcommitment) and perceived stress could be partially explained by the mediation of FFMQ facets (describing, observing, non-reactivity, non-judging, and acting with awareness). p values for the beta coefficients were obtained using Wald tests, and indirect effects were estimated using 5000 bootstrap samples.

Results

Preliminary Analyses

The results of the relationships between sociodemographic characteristics and perceived stress (PSS), Effort-Reward Imbalance (ERI-SQ), and trait mindfulness (FFMQ) are presented in Table 1. t test results indicate significant gender differences in perceived stress scores (PSS), with females showing significantly higher scores on average than males. There is a significant difference in mindfulness scores (FFMQ) between working and non-working students, with working students showing higher average scores. No other significant differences were found. Finally, according to the PSS categorization, 89.14% (n = 394) of the sample reported moderate and severe stress.

Table 1.

Sample Descriptives Using t Test for Equality of Means.

	PSS						ERI-SQ						FFMQ
	M	SD	df	t	p	d	M	SD	df	t	p	d	M	SD	df	t	p	d
Gender
Female	22.44	6.57	164.13	3.25	.001	0.38	1.06	0.34	148.92	0.07	.939	0.01	120.09	18.11	181.61	−1.26	.206	−0.14
Male	19.92	7.05	164.13	3.25	.001	0.38	1.06	0.42	148.92	0.07	.939	0.01	122.69	19.07	181.61	−1.26	.206	−0.14
Out of town
Yes	21.74	6.87	352.97	0.25	.797	0.02	1.07	0.39	328.68	1.01	.789	−0.03	121.66	18.99	355.89	−0.83	.403	−0.08
No	21.91	6.72	352.97	0.25	.797	0.02	1.06	0.34	328.68	1.01	.789	−0.03	120.12	18.79	355.89	−0.83	.403	−0.08
Working student
Yes	21.57	6.74	400.53	0.73	.465	0.07	1.04	0.35	409.61	1.74	.312	0.10	123.50	19.54	380.71	−2.63	.009	−0.25
No	22.05	6.79	400.53	0.73	.465	0.07	1.08	0.36	409.61	1.74	.312	0.10	118.69	18.13	380.71	−2.63	.009	−0.25

PSS Perceived Stress Scale, ERI-SQ Effort-Reward Imbalance Student-Questionnaire, FFMQ Five Facet Mindfulness Questionnaire, M Mean, SD Standard Deviation, df degree of freedom, p p-value, d Cohen’s d effect size.

ANOVA Analyses

The ANOVA analyses, as presented in Table 2, explored differences in perceived stress, effort-reward imbalance, and trait mindfulness scores between different academic and geographic demographic groups. A significant variation in PSS scores based on university location was observed, suggesting that geographical context can influence students’ perceived stress levels, however, post hoc comparisons using the Tukey HSD test showed no statistically significant differences between the locations overall. For the ERI-SQ, significant differences were found across academic fields, highlighting how fields of study influence the effort-reward ratio differently. Subsequently, post-hoc comparisons using the Tukey HSD test indicated that the mean score for the “Humanities and Social Sciences” field was significantly different than the “Health Sciences” field, with a difference of −0.127 (95% CI [-0.216, −0.0386], p = .001). In addition, university location also showed a significant impact, indicating that students in different regions may perceive their work and study environment differently. Tukey’s post-hoc tests showed that the mean score for “South and Islands” was significantly different from “Central”, with a difference of 0.1506 (95% CI [0.0182, 0.283], p = .021). Additionally, “South and Islands” was also significantly different from “North”, with a difference of 0.1822 (95% CI [0.0811, 0.283], p < .001). Finally, FFMQ differences based on educational attainment reached significance suggesting that educational attainment can influence mindfulness competence. Tukey’s post-hoc tests indicated significant differences in the FFMQ scores between those enrolled in a “bachelor’s degree” and “PhD”, with a difference of −20.70 (95% CI [-39.24, −2.152], p = .022). No other statistically significant differences were found between the groups and other variables.

Table 2.

Means, Standard Deviations, and One-Way Analyses of Variance in Sample Descriptives.

	PSS					ERI-SQ					FFMQ
	M	SD	df	F	η²	M	SD	df	F	η²	M	SD	df	F	η²
Academic fields
Health sciences	22.30	6.23	3, 438	0.41	.01	1.14	0.37	3, 438	5.76 ^***	.02	119.45	19.18	3, 438	0.67	.01
Scientific and technological	21.64	6.78				1.04	0.30				121.03	14.86
Humanities and social sciences	23.33	8.99				1.00	0.34				121.80	19.39
Other	21.87	6.63				1.19	0.51				117.50	16.81
University location
North	21.29	6.81	2, 439	3.33 ^*	.01	1.02	0.36	2, 439	8.99 ^**	.04	120.31	18.74	2, 439	0.48	.01
Center	22.97	6.42				1.07	0.32				122.83	20.75
South and islands	23.15	6.66				1.22	0.37				121.51	17.75
Education
Bachelor’s degree	22.36	6.60	3, 438	1.01	.01	1.05	0.33	3, 438	1.35	.01	118.88	17.79	3, 438	3.37 ^*	.02
Master’s degree	21.38	6.91				1.08	0.40				121.73	19.10
Master	22.50	6.87				0.91	0.31				124.20	26.73
PhD	19.71	7.23				0.89	0.30				139.57	21.37

PSS Perceived Stress Scale, ERI-SQ Effort-Reward Imbalance Student-Questionnaire, FFMQ Five Facet Mindfulness Questionnaire.

*p < .05. **p < .01.

Pearson Correlation Analyses

Pearson correlation analyses are presented in Table 3. The correlation between age and the other construct in the study shows that age is negatively and significantly correlated with PSS and ERI-SQ and positively correlated with FFMQ. Perceived stress and Effort-reward imbalance are significantly and negatively correlated with FFMQ and all its facets except for “Observing”. FFMQ and all its facets, except for “Observing”, significantly and negatively correlated with perceived stress and effort-reward imbalance. On the other hand, a positive significant correlation was found between perceived stress and effort-reward imbalance. Concerning the ERI-SQ subscales, Pearson’s correlation analyses found a positive correlation between the Perceived Stress Scale (PSS) score and effort and overcommitment. Inversely, these same factors showed a negative correlation with the Five Facet Mindfulness Questionnaire (FFMQ) score. On the other hand, the reward subscale was negatively correlated with PSS and positively correlated with FFMQ.

Table 3.

Descriptive Statistics and Correlations for Study Variables.

Variable	M	SD	1	2	3	4	5	6	7	8	9	10	11	12
1. Age	23.37	4.33	-
2. PSS	22.44	6.57	−0.10^* [−.19 −.01]	-
3. ERI-SQ	1.11	0.32	−0.01 [−.11, .08]	0.53^*** [.46, .60]	-
4. EFF	5.80	1.30	−0.26 [−.15, .03]	0.50^*** [.42, .56]	0.88^*** [.85, .90]	-
5. REW	13.30	1.60	−0.07 [-.17, .02]	−0.32^*** [−.41, −.24]	−0.64^*** [−.70, −.58]	−0.23^*** [−.32, −.14]	-
6. OV	12.75	2.33	−0.10^* [−.20 −.01]	0.44^*** [.36, .51]	0.44^*** [.36, .52]	0.50^*** [.41, .56]	−0.13^** [−.23, .03]	-
7. FFMQ	120.71	18.86	0.16^*** [.06, .25]	−0.57^*** [-.63, .51]	−0.36^*** [−.44, −.27]	−0.32^*** [−.40, −.24]	0.25^*** [.16, .34]	−0.31^*** [−.40, −.22]	-
8. OBS	25.00	5.48	0.06 [−.03, .16]	0.05 [−.04, 0.14]	−0.06 [−.15, .03]	−0.03 [−.12, .06]	0.10 [.01, .20]	0.08 [.02, .18]	0.34^*** [.26, .42]	-
9. DES	27.00	6.40	0.11^* [.02, .21]	−0.35^*** [−.43, .26]	−0.20^*** [−.29, −.11]	−0.15^*** [−.25, .06]	0.21^*** [.12, .30]	−0.17^*** [−.27, −.08]	0.73^*** [.68, .77]	0.19^*** [.09, .27]	-
10. NJ	24.60	7.32	0.15^** [.05, .24]	−0.48^*** [−.55, −.41]	−0.29^*** [−.37, −.20]	−0.30^*** [−.40, −.21]	0.13^** [.04, .23]	−0.40^*** [−.45, −.28]	0.72^*** [.67, .76]	−0.09 [−.18, .00]	0.33^*** [.24, .41]	-
11. NR	19.80	4.38	0.12^* [.03, .21]	−0.52^*** [−.58, −.44]	−0.21^*** [−.30, −.12]	−0.18^*** [−.27, −.10]	0.20^*** [.10, .26]	−0.24^*** [−.33, −.14]	0.63^*** [.57, .68]	0.17^*** [.08, .26]	0.31^*** [.22, .39]	0.41^*** [.33, .48]	-
12. AWA	24.40	6.18	0.05^* [−.04, .14]	−0.49^*** [−.57, −.43]	−0.33^*** [-.41, −.24]	−0.31^*** [−.40, −.22]	0.20^*** [.10, .28]	−0.24^*** [−.33, −.15]	0.69^*** [.64, .74]	−0.05 [−.14, .05]	0.42^*** [.34, .49]	0.46^*** [.38, .52]	0.25^*** [.16, .34]	-

M mean, SD standard deviation, PSS Perceived Stress Scale, ERI-SQ Effort-Reward Imbalance Student-Questionnaire, FFMQ Five Facet Mindfulness Questionnaire, EFF effort, REW reward, OV overcommitment, OBS observing, DES describing, NJ non-judging, NR non-reactivity, AWA acting with awareness.

^*p < .05.^**p < .01.^***p < .001.

Mediation Analysis

The model results are depicted in Table 4 and Figure 1. Before considering the influence of mediators, the direct effect of the Effort-Reward Imbalance Student Questionnaire (ERI-SQ) subscales on the Perceived Stress Scale (PSS) score was examined. The results showed that the effort (β = 1.470, p < .001) and overcommitment (β = 0.249, p = .041) scores both have a significant positive effect on perceived stress. In contrast, the reward score has a significant negative effect (β = −0.559, p < .001). Mediators from the subscales of the FFMQ were included in the mediation model. The effect of independent variables on mediators revealed that overcommitment positively influences observing (β = 0.349, p = .009), while reward has a positive effect on describing (β = 0.709, p = .001) and acting with awareness (β = 0.416, p = .034). Conversely, effort has a negative effect on acting with awareness (β = −0.911, p = .001). In addition, overcommitment negatively affects non-judging (β = −0.897, p < .001) and non-reactivity (β = −0.365, p = .002), while reward has a positive effect on non-reactivity (β = 0.305, p = .031).

Table 4.

Mediation Model, Indirect (Mediated) Effects. Dependent Variable: Perceived Stress.

Effect		β coefficient	SE	z	p
I.V.	Mediator	β coefficient	SE	z	p
Effort	Describing	−0.210	0.274	−0.768	.443
	Observing	−0.379	0.250	−1.513	.130
	Non reactivity	−0.092	0.209	−0.438	.661
	Non judging	−0.623	0.332	−1.876	.061
	Acting with awareness	−0.911	0.279	−3.263	.001
Reward	Describing	0.709	0.214	3.320	.001
	Observing	0.332	0.180	1.840	.066
	Non reactivity	0.305	0.141	2.162	.031
	Non judging	0.201	0.218	0.925	.355
	Acting with awareness	0.416	0.196	2.119	.034
Overcommitment	Describing	−0.308	0.166	−1.855	.064
	Observing	0.349	0.134	2.599	.009
	Non reactivity	−0.365	0.118	−3.104	.002
	Non judging	−0.897	0.168	−5.351	.001
	Acting with awareness	−0.304	0.157	−1.939	.053

Effort-Reward Imbalance - Student Questionnaires’ subscales Effort, Reward and Overcommitment (I.V.), Five Facet Mindfulness Questionnaires’ subscales Describing, Observing, Non reactivity, Non judging and Acting with awareness (Mediator), Perceived Stress (D.V.). SE Standard Error, z Goodman Test value, p probability value.

Figure 1.

Mediation analysis for perceived stress. Note: red lines represent significant negative relationships; green lines represent significant positive relationships; grey dotted lines represent a non - significant relationships.

Direct effects of mediators on PSS score showed that observing (β = 0.134, p = .003) has a significant positive effect on perceived stress while describing (β = −0.101, p = .022), acting with awareness (β = −0.203, p < .001) and non-reactivity (β = −0.513, p < .001) have significant negative effects. Non judging showed no significant effect on the PSS score (β = −0.070, p = .076). The indirect effects of the independent variables on the dependent variable through the mediators revealed that the indirect effect of effort is not significant (β = 0.246, p = .134), while the indirect effect of reward is significant and negative (β = −0.282, p = .013). The indirect effect of overcommitment is significant and positive (β = 0.390, p < .001). Finally, the total effects showed that the total effect of effort (β = 1.716, p < .001) and overcommitment (β = 0.639, p < .001) on the PSS score remain significant, indicating partial mediation. The total effect of reward on the PSS score also remains significant and negative (β = −0.841, p < .001), suggesting partial mediation.

Discussion

This research focused on the exploration of perceived stress, trait mindfulness, and effort-reward imbalance in a sample of Italian university students to investigate the relationship between variables. Compared to other studies in the literature, this is the first study to compare effort-reward imbalance with trait mindfulness in a sample of Italian university students. Although most studies on an Italian sample investigate perceived stress in university students about other constructs (Caso et al., 2020; Concerto et al., 2017; Magnavita & Chiorri, 2018; Porru et al., 2022), few studies have included effort-reward imbalance in their research (Porru et al., 2021; Portoghese et al., 2019). In addition, it is important to note that some studies have focused only on university students in a specific academic area, often healthcare (Concerto et al., 2017; Magnavita & Chiorri, 2018). For example, a multicenter cross-sectional study conducted on a sample of nursing students from northern Italy investigated the psychological predictors of stress (Salvarani et al., 2020). The study found that 70% of the sample exhibited high levels of stress, while trait mindfulness was associated with lower levels of psychological distress (Salvarani et al., 2020).

In the present study, it was found that working students show greater trait mindfulness than non-working students and this trait varies significantly according to the student’s subject area. Additionally, a statistically significant difference was found between perceived stress and effort-reward imbalance scores depending on the location of the university attended by students, with higher scores in the South and Islands. In the sample, a higher age was associated with a lower perception of stress and a higher trait of mindfulness. Perceived stress correlates positively with effort-reward imbalance, while both variables correlate negatively with trait mindfulness.

Regarding the mediation analysis, the results suggest that mindfulness facets act as partial mediators in the relationship between ERI-SQ subscales and perceived stress. The effort has a significant direct impact on perceived stress, even when considering mediators, indicating that factors other than mindfulness may be involved in explaining this relationship. Reward and overcommitment show that their direct effects on perceived stress are small but remain significant when considering mediators, suggesting that mindfulness facets contribute partly but not completely to explaining these effects. However, the low internal consistency of the reward and overcommitment subscales of the ERI-SQ should be considered when interpreting these findings. This limitation may have reduced the ability of the ERI-SQ to fully capture the effort-reward imbalance construct, potentially affecting the strength and reliability of the observed relationships. Future studies should aim to validate and refine these subscales to ensure robust psychometric properties in academic contexts.

Furthermore, as this study employed a cross-sectional design, it is not possible to establish causal relationships between effort-reward imbalance, mindfulness, and perceived stress. The observed associations may also be influenced by unmeasured confounding variables, underscoring the need for longitudinal research to explore the temporal dynamics of these relationships. Despite these limitations, the findings provide valuable insights into the potential role of mindfulness in mitigating academic stress and suggest promising directions for future research and interventions.

Limitations and Future Implications

Firstly, the cross-sectional design of our data precludes the establishment of causal relationships between the examined demographic and psychosocial variables and psychological distress. Secondly, the limited sample size and, notably, the recruitment from Italian universities might have implications for the external validity of our findings. The narrowed sample size might indeed increase the risk of sampling biases due to voluntary recruitment and exclusion of participants. The assessment measures employed were all self-report instruments, with participants’ responses all subjected to social desirability, over- or underestimation of one’s abilities and attitudes, and memory bias. Additionally, as outlined by Portoghese et al. (2019) and Porru et al. (2022), the ERI-SQ reward subscale is only constituted by two items, suffering from limitations that might hinder the identification of factors in factorial analyses. Such scarcity could restrict the instrument’s capacity to grasp all facets of the dimensions of reward, overcommitment, and effort. Furthermore, coefficients of internal consistency of the effort subscale were not reported, as well as test-retest reliability (Portoghese et al., 2019). Information regarding the calculation of scores for all three subscales is missing, with details on scoring only for the overcommitment and reward scale, compromising the chance to calculate a score considering also the effort subscale, and therefore limiting its use in research and clinical contexts. Further studies are needed to test the validity of such a scale, also broadening the spectrum of items of effort, reward, and overcommitment subscales. Implications for future research would entail the conceptualization and validation of new theoretical models that might consider the role of gender and other socio-demographic factors in influencing the relation between effort-reward imbalance and perceived stress, also broadening the sample to various academic populations and cultural settings.

As for the outcomes of the mediation analysis, the mediation model did not consider the influence that various variables could have exerted, such as diverse locations, academic field, and background education, hindering therefore potential generalizability within a broader population of Italian students that surpasses the context of Northern Italy. However, according to the official data of the Italian Ministry of University and Research (USTAT, nd), the majority of Italian students are enrolled at universities located in the Northern regions of Italy. Further studies should consider the impact of variables such as background education, the type of academic field and the location, alongside a sample that is more representative of the whole student population across Italian regions. From an institutional standpoint, the study suggests the potential role universities might play in fostering the implementation of well-being programs that promote mindfulness-based interventions to reduce stress and ease a balance between perceived academic effort and reward. Lastly, with further studies investigating the role of trait mindfulness as a potentially protective factor against academic strain and distress, preventative measures and instruments can be implemented to screen and advise for subjects at higher risk for heavy academic mental load and stress in favor, again, of the teaching of mindfulness abilities and techniques to ease stress.

Conclusions

Our work on a sample of Italian students, confirms evidence from previous studies on high levels of academic stress among university students and statistically significant differences between genders. To cope with the academic stress of university students, which can have repercussions on students’ academic careers and personal lives, academic institutions should pay more attention to students’ health. Mindfulness-based interventions may offer an effective solution to be implemented in the form of courses, workshops, or digital apps, to help students increase mindfulness facets and reduce academic stress. Furthermore, future studies could employ a longitudinal design with a more geographically and academically homogenous sample of Italian students to provide deeper insights into the dynamics of trait mindfulness and academic stress over time, especially following mindfulness interventions.

Footnotes

Author Contributions

A.O. and S.C. conceived the study. A.O. conducted the quantitative study, prepared the database, and analysed the data under the supervision of S.G5 and G.M. A.O. and S.C. drafted the first manuscript. G.M., S.d.P., S.G4, A.F., and A.R. revised the first draft. All authors contributed substantially to the interpretation of the data and the successive versions of the manuscript. All authors contributed to the manuscript and approved its final version. RGG is the principal investigator of the study.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Ethical Statement

ORCID iDs

Alessandro Ocera

Sofia Colombo

Data Availability Statement

The dataset used and analyzed during the current study is available from the corresponding author upon reasonable request.

Appendix

Author Biographies

Alessandro Ocera (Msc and PhD Fellow): Alessandro holds a Master of Science in Digital Psychology, and is a PhD Fellow at Sigmund Freud University, Milan (Italy). He is also a Mindfulness-Based Stress Reduction (MBSR) Teacher Trainer. Alessandro's research focus areas are quantitative research on the efficacy of Cognitive Behavioral Therapy (CBT) on personality disorders and maladaptive personality traits. Alessandro is also interested in the application of new technologies in the field of clinical psychology and scientific research.

Sofia Colombo (MSc): Sofia holds a Master of Science in Digital Psychology and is currently pursuing an internship in Global Corporate HR. Her research interests cover the broad topic of organizational behavior and well-being, and stress management.

Sonia de Paz-Cantos (MSc and PhD Candidate): Sonia is a biologist specializing in Epidemiology and Health Management. She is currently in the final stage of her PhD on the use of screens (smartphones and tablets) in children and pre-adolescents. During her pre-doctoral stage, she has spent time abroad, specifically in Australia, where research on the use of screens is pioneering.

Antonella Frisiello (MSc, Eur.Erg.): Antonella is a clinical psychologist and cognitive ergonomist with extensive expertise in human-centered design and user experience. She is a senior researcher at LINKS Foundation, focusing on data science applications for industrial and societal innovation.

Silvia Gilotta (PhD, Eur.Erg.): Silvia is a psychologist and cognitive ergonomist with a PhD in Applied Psychology. She is the founder of Adequat s.r.l. and specializes in UX research, human-computer interaction, and ergonomic design for industrial and digital applications.

Silvia Grazioli (MSc and PhD Candidate): Silvia is a psychologist and biostatistician. She is currently a PhD Candidate at Sigmund Freud University, Milan.

Giovanni Michelini (PhD): Giovanni is a Tenured Lecturer in Statistics and Quantitative Methods, founder and director of the Artificial Intelligence and Data Analysis (AIDA) Lab at Sigmund Freud University, Milan and Psychometrician at Department of Disabilities of Fondazione Istituto Ospedaliero di Sospiro – ONLUS.

Antonella Roella (MSc, Eur.Erg.): Antonella is a cognitive ergonomist with extensive experience in user experience (UX) and usability research.

Regina Gregory Grgič (PhD): Regina is Director of the Digital Psychology Lab, Coordinator of the curriculum in Digital Psychology of the Master ’s Course in Psychology and Tenured Lecturer in Research Methodology at Sigmund Freud University, Milan.

References

APA Dictionary of Psychology . (2018). https://dictionary.apa.org/stress

Baer

R. A.

Smith

G. T.

Hopkins

Krietemeyer

Toney

(2006). Using Self-Report assessment methods to explore facets of mindfulness. Assessment, 13(1), 27–45. https://doi.org/10.1177/1073191105283504

Barbayannis

Bandari

Zheng

Baquerizo

Pecor

K. W.

Ming

(2022). Academic stress and mental well-being in college students: Correlations, affected groups, and COVID-19. Frontiers in Psychology, 13(1), Article 886344. https://doi.org/10.3389/fpsyg.2022.886344

Bergin

Pakenham

(2016). The stress-buffering role of mindfulness in the relationship between perceived stress and psychological adjustment. Mindfulness, 7(4), 928–939. https://doi.org/10.1007/S12671-016-0532-X

Brown

K. W.

Ryan

R. M.

(2003). The benefits of being present: Mindfulness and its role in psychological well-being. Journal of Personality and Social Psychology, 84(4), 822–848. https://doi.org/10.1037/0022-3514.84.4.822

Cash

Whittingham

(2010). What facets of mindfulness contribute to psychological well-being and depressive, anxious, and stress-related symptomatology? Mindfulness, 1(3), 177–182. https://doi.org/10.1007/s12671-010-0023-4

Caso

Miriam

Rosa

Mark

(2020). Unhealthy eating and academic stress: The moderating effect of eating style and BMI. Health Psychology Open, 7(2), Article 2055102920975274. https://doi.org/10.1177/2055102920975274

Cohen

(1988). Perceived stress in a probability sample of the United States. In Spacapan

Oskamp

(Eds.), The social psychology of health (pp. 31–67). Sage Publications, Inc.

Cohen

Kamarck

T. W.

Mermelstein

R. J.

(1983). A global measure of perceived stress. Journal of Health and Social Behavior, 24(4), 385–396. https://doi.org/10.2307/2136404

10.

Concerto

Patel

Infortuna

Chusid

Muscatello

M. R.

Bruno

Zoccali

Aguglia

Battaglia

(2017). Academic stress disrupts cortical plasticity in graduate students. Stress: The International Journal on the Biology of Stress, 20(2), 212–216. https://doi.org/10.1080/10253890.2017.1301424

11.

Coutts-Smith

J. R.

Phillips

W. J.

(2023). The role of trait mindfulness in the association between loneliness and psychological distress. Mindfulness, 14(8), 1980–1996. https://doi.org/10.1007/s12671-023-02184-7

12.

Fossati

(2010). Italian perceived stress scale. Available at: https://www.cmu.edu/dietrich/psychology/stress-immunity-disease-lab/scales/index.html

13.

Giovannini

Giromini

Bonalume

Tagini

Lang

Amadei

(2014). The Italian five facet mindfulness questionnaire: A contribution to its validity and reliability. Journal of Psychopathology and Behavioral Assessment, 36(3), 415–423. https://doi.org/10.1007/s10862-013-9403-0

14.

Hodge

Wright

Bennett

(2020). Balancing effort and rewards at university: Implications for physical health, mental health, and academic outcomes. Psychological Reports, 123(4), 1240–1259. https://doi.org/10.1177/0033294119841845

15.

Kim

Lee

S. M.

(2017). Examining longitudinal relationship among effort reward imbalance, coping strategies and academic burnout in Korean middle school students. School Psychology International, 38(6), 628–646. https://doi.org/10.1111/imm.12804

16.

Liu

Wei

Cheng

(2022). Depression and anxiety from acculturative stress: Maladaptive perfectionism as a mediator and mindfulness as a moderator. Asian American Journal of Psychology, 13(2), 207–216. https://doi.org/10.1037/aap0000242

17.

Magnavita

Chiorri

(2018). Academic stress and active learning of nursing students: A cross-sectional study. Nurse Education Today, 68(1), 128–133. https://doi.org/10.1016/j.nedt.2018.06.003

18.

Martínez-Rubio

Colomer-Carbonell

Sanabria-Mazo

J. P.

Pérez-Aranda

Navarrete

Martínez-Brotóns

Escamilla

Muro

Montero-Marín

Luciano

J. V.

Feliu-Soler

(2023). How mindfulness, self-compassion, and experiential avoidance are related to perceived stress in a sample of university students. PLoS One, 18(2), Article e0280791. https://doi.org/10.1371/journal.pone.0280791

19.

Medvedev

O. N.

Norden

P. A.

Krägeloh

C. U.

Siegert

R. J.

(2018). Investigating unique contributions of dispositional mindfulness facets to depression, anxiety, and stress in general and student populations. Mindfulness, 9(6), 1757–1767. https://doi.org/10.1007/s12671-018-0917-0

20.

Metzger

I. W.

Blevins

Calhoun

C. D.

Ritchwood

T. D.

Gilmore

A. K.

Stewart

Bountress

K. E.

(2017). An examination of the impact of maladaptive coping on the association between stressor type and alcohol use in college. Journal of American College Health: J of ACH, 65(8), 534–541. https://doi.org/10.1080/07448481.2017.1351445

21.

Porru

Robroek

S. J.

Bültmann

Portoghese

Campagna

Burdorf

(2021). Mental health among university students: The associations of effort-reward imbalance and overcommitment with psychological distress. Journal of Affective Disorders, 282(1), 953–961. https://doi.org/10.1016/j.jad.2020.12.183

22.

Porru

Schuring

Bültmann

Portoghese

Burdorf

Robroek

S. J.

(2022). Associations of university student life challenges with mental health and self-rated health: A longitudinal study with 6 months follow-up. Journal of Affective Disorders, 296(1), 250–257. https://doi.org/10.1016/j.jad.2021.09.057

23.

Portoghese

Galletta

Porru

Burdorf

Sardo

D’Aloja

Finco

Campagna

(2019). Stress among university students: Factorial structure and measurement invariance of the Italian version of the effort-reward imbalance student questionnaire. BMC Psychology, 7(1), 68. https://doi.org/10.1186/s40359-019-0343-7

24.

Posit Team . (2024). RStudio: Integrated development environment for R (version 2024.04.1+748). Posit Software, PBC. https://posit.co

25.

Prowse

Sherratt

Abizaid

Gabrys

R. L.

Hellemans

K. G. C.

Patterson

Z. R.

McQuaid

R. J.

(2021). Coping with the COVID-19 pandemic: Examining gender differences in stress and mental health among university students. Frontiers in Psychiatry, 12(1), Article 650759. https://doi.org/10.3389/fpsyt.2021.650759

26.

R Core Team . (2024). R: A language and environment for statistical computing. R Foundation for Statistical Computing.

27.

Revelle

(2024). psych: Procedures for psychological, psychometric, and personality research. Northwestern University. R package version 2.4.6. https://CRAN.R-project.org/package=psych

28.

Rosseel

(2012). lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48(2), 1–36. https://doi.org/10.18637/jss.v048.i02

29.

Salvarani

Ardenghi

Rampoldi

Bani

Cannata

Ausili

Di Mauro

Strepparava

M. G.

(2020). Predictors of psychological distress amongst nursing students: A multicenter cross-sectional study. Nurse Education in Practice, 44(1), Article 102758. https://doi.org/10.1016/j.nepr.2020.102758

30.

Selye

(1946). The general adaptation syndrome and the diseases of adaptation. The Journal of Clinical Endocrinology & Metabolism, 6(2), 117–230. https://doi.org/10.1210/jcem-6-2-117

31.

Siegrist

(1996). Adverse health effects of high-effort/low-reward conditions. Journal of Occupational Health Psychology, 1(1), 27–41. https://doi.org/10.1037/1076-8998.1.1.27

32.

Siegrist

Starke

Chandola

Godin

Marmot

Niedhammer

Peter

(2004). The measurement of effort–reward imbalance at work: European comparisons. Social Science and Medicine, 58(8), 1483–1499. https://doi.org/10.1016/s0277-9536(03)00351-4

33.

State of New Hampshire Employee Assistance Program . (nd). Perceived stress scale. Retrieved from. https://www.das.nh.gov/wellness/Docs%5CPercieved_Stress_Scale.pdf

34.

USTAT . (nd). Esplora i dati. USTAT. https://ustat.mur.gov.it/dati/didattica/italia/atenei

35.

van Vegchel

De Jonge

Bosma

Schaufeli

W. B.

(2005). Reviewing the effort–reward imbalance model: Drawing up the balance of 45 empirical studies. Social Science and Medicine, 60(5), 1117–1131. https://doi.org/10.1016/j.socscimed.2004.06.043

36.

Wege

Muth

Angerer

Siegrist

(2017). Student ERI: Psychometric properties of a new brief measure of effort-reward imbalance among university students. Journal of Psychosomatic Research, 94(1), 64–67. https://doi.org/10.1016/j.jpsychores.2017.01.008

37.

Weinstein

Brown

Ryan

(2009). A multi-method examination of the effects of mindfulness on stress attribution, coping, and emotional well-being. Journal of Research in Personality, 43(3), 374–385. https://doi.org/10.1016/J.JRP.2008.12.008

38.

Williams

Dziurawiec

Heritage

(2017). More pain than gain: Effort–reward imbalance, burnout, and withdrawal intentions within a university student population. Journal of Educational Psychology, 110(3), 378–394. https://doi.org/10.1037/edu0000212

39.

World Health Organization (WHO) . (2023). Stress. https://www.who.int/news-room/questions-and-answers/item/stress

40.

Shi

Huang

Fan

(2021). Longitudinal relationship between emotional insecurity and adolescent mental health: The mediation of rejection sensitivity and moderation of dispositional mindfulness. Mindfulness, 12(11), 2662–2671. https://doi.org/10.1007/s12671-021-01727-0

41.

Zahra

S. T.

Riaz

(2017). Mediating role of mindfulness in stress-resilience relationship among university students. Pakistan Journal of Psychology, 48(2), 21–32.

42.

Zimmaro

Salmon

Naidu

Rowe

Phillips

Rebholz

Giese-Davis

Cash

Dreeben

Bayley-Veloso

Jablonski

Hicks

Siwik

Sephton

(2016). Association of dispositional mindfulness with stress, cortisol, and well-being among university undergraduate students. Mindfulness, 7(4), 874–885. https://doi.org/10.1007/S12671-016-0526-8