Job crafting and its role in fostering personal resources and adaptation to change in the context of a pandemic

Signore, Fulvio; Ingusci, Emanuela; De Carlo, Elisa; Catalano, Alessia Anna; Cortese, Claudio Giovanni; Ciavolino, Enrico

doi:10.3389/forgp.2025.1576289

ORIGINAL RESEARCH article

Front. Organ. Psychol., 26 June 2025

Sec. Employee Well-being and Health

Volume 3 - 2025 | https://doi.org/10.3389/forgp.2025.1576289

Job crafting and its role in fostering personal resources and adaptation to change in the context of a pandemic

Fulvio Signore¹

Emanuela Ingusci²

Elisa De Carlo²^*

Alessia Anna Catalano³

Claudio Giovanni Cortese⁴

Enrico Ciavolino^2,5

¹Department of Human and Social Sciences, Mercatorum University, Rome, Italy
²Department of Human and Social Sciences, University of Salento, Lecce, Italy
³Department of Law Studies, University of Salento, Lecce, Italy
⁴Department of Psychology, University of Turin, Turin, Italy
⁵Department of Computer Science and New Technology, WSB University, Gdańsk, Poland

Introduction: Over the last few decades, various strategies have been investigated, in order to improve workers' wellbeing by empowering workers themselves as agents of change. The individual processes enabling workers to shape their professional context to better suit their needs include job crafting, a bottom-up strategy associated with numerous positive outcomes. The COVID-19 pandemic induced significant changes in the work environment, indirectly prompting workers to find new ways to manage their tasks. This study draws on the theoretical framework provided by the Job Demands-Resources model to examine the relationships between job crafting, job resources—specifically self-efficacy and positive emotions—and strategies to cope with organizational change.

Methods: To achieve this objective, analyses were conducted using Partial Least Squares Structural Equation Modeling (PLS-SEM) and validated through 5,000 bootstrap resamples. A sample of 782 workers, selected through non-probabilistic convenience sampling, completed a questionnaire between May and July 2020. Variables measured included personal resources, such as self-efficacy and positive emotions, job crafting, age, and coping with organizational change, assessed via several items drawn from validated scales.

Results: The findings showed that, during the pandemic, job crafting played a significant role in enhancing personal resources, as defined by the Job Demands-Resources model, promoting growth processes and facilitating adaptation to change.

Discussion: From a practical perspective, job crafting proved to be an important strategy for activating positive psychological and emotional resources, even during periods of extreme turbulence and transformation. The practical implications and limitations of the study are discussed.

1 Introduction

The professional world is characterized by evolving dynamics that compel workers to constantly face unexpected and sudden changes. The COVID-19 pandemic amplified the concerns and issues inherent in the work environment, regardless of cultural context (Esposito et al., 2022). As a result, scholarly interest in the relationship between pandemic-induced changes and the work environment has grown (Kniffin et al., 2021). An increasing number of studies have investigated such a relationship, as the pandemic affected both the world of work and workers' responses to transformations in the workplace. Research has shown that the COVID-19 pandemic made some jobs more challenging, due to increased workload, emotional strain, and technological stress, while simultaneously reducing key resources such as autonomy and social support. This led to an imbalance that workers had to actively manage.

In this context, substantial research has focused on job crafting, a specific form of individual work management that, being closely tied to meeting personal needs and requirements, proved crucial in dealing with pandemic-induced changes. A study by Pijpker et al. (2022) has demonstrated that the different sub-dimensions of job crafting played a protective role against burnout and correlated negatively with it. Research by Månsson Sandberg et al. (2024) has found that job crafting was also a significant tool in healthcare settings, as it offered essential insights for managing one's own work. Results from Ingusci et al. (2021) have revealed that the “active” sub-dimensions of job crafting acted as a powerful mediating mechanism in reducing workers' behavioral stress. Findings from Zampetakis (2023) have supported these results, showing that seeking challenges—a dimension of job crafting—functioned as an effective coping strategy to face pandemic-related fears, simultaneously enhancing work engagement. Drawing on the Job Demands-Resources (JD-R) model, job crafting has been conceptualized as a proactive strategy that enables workers to restore balance between job demands and available resources. By increasing structural and social resources, seeking new challenges, and reducing hindering demands, employees could actively mitigate the increased stress and uncertainty experienced during the pandemic.

Starting from Elton Mayo's ideas (Bruce and Nyland, 2011), which revolved around the Human Relations School of thought, a shift occurred in the way workers were regarded when performing their roles. As they gradually came to be seen as more than a simple element in an assembly line (Taylor, 2004; Argentero and Cortese, 2018), their psychological and motivational dimensions began to be recognized as crucial. This paradigm shift aligns with contemporary approaches that focus not only on productivity but also on wellbeing, such as those embedded in the concepts of decent work and healthy organizations. The concept of decent work defines the fundamental attributes of work that encapsulate the four strategic objectives of the International Labor Organization (ILO): “promotion of rights at work, employment, social protection and social dialogue” (Larion, 2013). This perspective reflects the idea that work should not only be a means of livelihood, but also a source of dignity, self-fulfillment, and social inclusion. The concept of healthy organizations expands this vision by emphasizing the interconnection between individual wellbeing, organizational performance, and broad socioeconomic outcomes. A healthy organization not only prioritizes the physical and psychological health of its employees, but also actively cultivates a work environment based on engagement, ethical leadership, participatory decision-making, and development of human potential. This approach recognizes that organizations thrive when employees experience meaningful work, supportive social relations, and a sense of purpose. It is within this context that recent reflections have highlighted how, starting from a framework that emphasizes the active role of individual positive resources (which are measurable, as noted by positive psychology) (Seligman and Csikszentmihalyi, 2014), it is possible to improve individual lives, organizations in general, financial productivity, and the financial sector. When organizations integrate the principles of decent work and healthy organizations, they contribute not only to employee satisfaction and motivation, but also to increased innovation, resilience, and long-term economic sustainability. Consequently, investigating all the factors that can foster improvement—both at individual and collective levels—becomes essential for creating workplaces that promote human flourishing while simultaneously enhancing organizational effectiveness (Seligman and Csikszentmihalyi, 2014; Luthans, 2002; Di Fabio, 2017; Salanova et al., 2013).

From this perspective, job crafting is an individual strategy based on self-initiated behavioral change that employees engage in, with the aim of aligning their jobs with personal preferences, motives, and passions (Wrzesniewski and Dutton, 2001). It can foster wellbeing and support the development of sustainable competences. As a psychological construct, it reflects a worker's proactive desire to modify the tangible boundaries of their work, in order to adapt what they are required to do to their individual needs and necessities (Wrzesniewski and Dutton, 2001; Tims et al., 2012). Job crafting can be considered a strategy that contrasts with traditional work reorganization approaches, which involve simplifying or enriching work activities and content to enhance motivation. Although such strategies can promote the development of professional competences and efficiency, over time, they may lead to static outcomes, due to the monotony and repetition of professional tasks. More recently, research has started to investigate how employees proactively reshape the characteristics of their jobs and work situations (Dash and Vohra, 2020; Petrou and Xanthopoulou, 2021). Proactive behavior at work seeks to improve the fit between individuals and their organizations, offering increased opportunities to prove personal strengths (Bakker et al., 2020; Bakker and de Vries, 2021). Therefore, job crafting is a new approach to job design that differs from the traditional models adopted by organizations. It refers to a series of bottom-up, self-oriented behaviors aimed at planning or redesigning work, empowering employees to construct their own autonomy and recognizing personal differences in a way that allows everyone to perform their own professional tasks (Arachie et al., 2021). Thanks to job crafting, workers are no longer passive recipients of assigned work tasks, as they can actively adapt and modify them based on their own competences, values, and interests (He, 2021). Job crafting can be described as a multidimensional construct whose ultimate aim is “to improve the overall experience and meaning that employees attribute to their work” (Böhnlein, 2021; Zampetakis, 2021).

The literature highlighting the role of job crafting in providing beneficial and coping mechanisms for managing pandemic-induced changes is well-developed, with this study aligning with previous research. However, while job crafting has been predominantly conceptualized as a mediator or moderator (Zampetakis, 2023; Miraglia et al., 2017; Robledo et al., 2019; Weber, 2019), it is here considered a predictor in relation to other variables. By adopting a theoretical framework grounded in positive psychology (Seligman and Csikszentmihalyi, 2014; Salanova et al., 2013), this study explores the role of this construct in fostering positive outcomes.

2 Theoretical framework: the job demands-resources model and the positive role of job crafting

The starting point of this research is the Job Demands-Resources model (Bakker and Demerouti, 2017; Bakker et al., 2023). Designed as a conceptual framework to explore and explain the development of motivational processes and health deterioration in the workplace, it has become one of the most flexible and useful models in the work environment, being recently extended to other sectors, such as training. This model has also been used to investigate workplace dynamics that emerged during and after the COVID-19 pandemic (Shamsi et al., 2021; Bilotta et al., 2021; Meyer et al., 2021). As numerous studies have shown, the COVID-19 pandemic had a crucial impact on the organization of work and the way tasks were performed, regardless of profession (Ratten, 2020; Barouki et al., 2021). Over the past few years, phenomena such as technostress (Ingusci et al., 2021; Molino et al., 2020) have been increasingly described as direct consequences of the pandemic. A further factor of change was the growing reliance on remote work (Donati et al., 2021; Galanti et al., 2021; Ingusci et al., 2019), which brought both benefits and drawbacks. The widespread use of new technologies and alternative forms of work also affected work-life balance (Vaziri et al., 2020) and detachment from work activities, a crucial component of recovery (Kniffin et al., 2021). All of these aspects both positively and negatively impacted work and organizational contexts, radically transforming them and leading workers to deal with unprecedented planning and needs, regardless of their roles (Gavin et al., 2022). Due to the effects of the pandemic on the world of work, a shift in management occurred, with workers taking spontaneous and individual actions to manage change and adapt tasks to their personal needs and requirements, which is the essence of job crafting (Pijpker et al., 2022).

Within the JD-R model, job crafting is described as a behavior aimed at balancing job demands and available resources (Bakker and de Vries, 2021, p. 202, Bakker and Demerouti, 2017; Bakker et al., 2023). Four measurable dimensions of job crafting have been identified: increasing structural job resources, increasing social job resources, increasing challenging job demands, and decreasing hindering job demands. Increasing structural job resources involves a self-directed development process of individual competences and autonomy in making decisions on task execution. Increasing social job resources includes behaviors such as seeking feedback or support from colleagues and managers. Increasing challenging job demands encompasses engaging with new tasks and taking on increased responsibilities. Decreasing hindering job demands is a reduction or avoidance strategy, which refers to efforts to reduce the impact of excessive job demands, such as work overload or emotionally demanding interactions with clients (Böhnlein, 2021; Dust and Tims, 2020). In the context of the JD-R model, the COVID-19 pandemic can be interpreted as a period marked by a significant increase in job demands (e.g., technological pressure, workload, emotional labor) and a simultaneous reduction in job resources (e.g., autonomy and social support). In this sense, job crafting becomes a proactive, problem-focused strategy to restore balance by reducing demands and increasing resources.

In line with the theoretical JD-R model, several studies have confirmed the relationship between job crafting behaviors and different work-related constructs. In a literature review on the topic, Böhnlein (2021) has investigated the effects of job crafting on wellbeing from both hedonic and eudaimonic perspectives. The hedonic perspective describes wellbeing in terms of subjective affective states, including job satisfaction, whereas the eudaimonic perspective defines it in relation to indicators of human functioning, such as work commitment and burnout. Most studies have highlighted a positive association between job crafting behaviors and perceived wellbeing, the meaning attributed to work, and self-image in the workplace (Ingusci et al., 2021; Böhnlein, 2021; Ingusci et al., 2019). Both task crafting and relational crafting seem to positively contribute to perceived wellbeing, the meaning attributed to work, and self-image in the workplace.

This can be explained by the fact that successful job crafting efforts provide workers with a sense of competence and effectiveness, reinforcing their personal beliefs in their ability to manage tasks and adapt to change. At the same time, job crafting enhances experiences of meaning, autonomy, and connection, which can generate positive emotions. These, in turn, support motivation, broaden coping capacity, and foster greater adaptability.

Employees who engage in task crafting behaviors focus on their own abilities and personal interests. Consequently, they may receive positive feedback and develop confidence through their crafting efforts. In this sense, task crafting acts as an indirect mechanism for enhancing wellbeing, a coping strategy to combat boredom at work. Through behaviors aimed at relational crafting, employees can also shape their social interactions, making them more stimulating and satisfying, which in turn improves their personal experiences and perception of wellbeing in the workplace (Böhnlein, 2021).

In light of these considerations, this paper aims to examine the role that job crafting played during the COVID-19 pandemic in both increasing personal resources, such as self-efficacy and positive emotions, and fostering change, in line with the theoretical framework provided by the Job Demands-Resources model, which has been widely applied in previous research. Although a number of studies have already explored the beneficial effects of job crafting on various job-related outcomes, few—partly due to the short time elapsed—have investigated whether these effects persist or intensify during periods of extreme turbulence and change, such as a pandemic.

2.1 The role of self-efficacy in growth processes

The construct of self-efficacy, also known as personal efficacy, originates from Bandura's Social Cognitive Theory (SCT) and refers to an individual's belief in themselves and their ability to display behaviors that are essential for exercising control and human agency. Self-efficacy reflects the conviction that individuals can succeed thanks to their belief in their ability to organize and perform the actions necessary to achieve specific outcomes or objectives in a given context (Adamovic et al., 2022). This construct applies to, and benefits, several domains, including task performance, relationships, and leadership. Self-efficacy may be developed through four primary sources (Bandura, 1986, 1997):

i) Mastery experiences: individuals gain confidence in their competences through direct experience;

ii) Vicarious experiences: individuals develop their competences indirectly, through the observation and imitation of other individuals who are taken as role models;

iii) Verbal persuasion: encouragement and support from an expert, such as a supervisor, can bolster self-efficacy, by influencing one's cognitive dimension;

iv) Physiological and emotional states: learning to manage and reinterpret negative emotions, such as anxiety, can reduce their detrimental impact on performance and support a more self-efficacious mindset.

Empirically, self-efficacy has proven to be a reliable indicator of an individual's real abilities. Stajkovic and Luthans (1998) have identified this construct as one of the most trustworthy predictors of performance in the workplace, showing the strong connection between the belief in one's ability to achieve results and actual achievement. Other studies have highlighted that self-efficacy may act as a mediating variable in relation to factors such as intelligence, personality traits (Chen et al., 2001; Judge et al., 2007), and performance (Tian et al., 2019). Further research has suggested that the effect of self-efficacy on performance can be mediated by job crafting (Miraglia et al., 2017). Beliefs in self-efficacy have also been positively correlated with innovative behaviors and learning in the workplace (Van Dam and Seijts, 2007), employees' involvement in developing activities (Bezuijen, 2005) and proactive engagement in tasks beyond their formal role (Parker et al., 2006; Tims et al., 2014), career development (Abele and Spurk, 2009; Smith and Betz, 2000), and performance success (Alessandri et al., 2015b). Beliefs in self-efficacy have been found to play a crucial role in strengthening an individual's connection to their organization (Borgogni et al., 2009), as they enhance perceived contribution, foster positive self-evaluation within the organizational context, and—more generally—support the development of constructive relationships with key organizational figures (Borgogni et al., 2010). Confidence in one's ability to succeed becomes important also for personal wellbeing, helping an individual to both experience a more positive connection to their job (Petrou and Xanthopoulou, 2021; Xanthopoulou et al., 2007a,b) and better resist stress and burnout (Consiglio et al., 2013).

The role of self-efficacy was extensively explored during the pandemic, when this construct became particularly relevant in relation to specific phenomena that started to occur more frequently. A study by Kondratowicz et al. (2022) has shown that remote working contributed to increased self-efficacy, which in turn had a positive effect on both life and job satisfaction. Research by Joie-La Marle et al. (2021) has also revealed that, during the pandemic, self-efficacy served as a protective factor against the risk of work-related depression and encouraged the expression of positive emotions.

Therefore, based on the abovementioned literature, the first hypothesis was formulated:

H1: Job crafting positively influences self-efficacy, positive emotions (personal resources), and coping with organizational change.

2.2 Emotions in the organizational context

The study of emotions in the organizational context was long overlooked, due to research focusing on other dimensions of organizational dynamics. However, Weiss and Cropanzano's Affective Events Theory (Weiss and Cropanzano, 1996) marked a turning point, proposing that emotions play a key role in the organizational context: when “affective events” occur in the workplace, they elicit affective responses (or emotions), which in turn influence attitudes and behaviors.

To systematize the role of emotions in the organizational context, Ashkanasy (2003) developed a five-level model that integrates the various ways in which emotions influence workers. Despite being different, such levels are interdependent. At the intra-individual level, temporal fluctuations in the emotions of an individual—or rather, of each member of an organization—are crucial. As research by Weiss and Cropanzano (1996) has also suggested, it is at this level that everyday positive or negative “affective events” interact with individual responses. The management of such events shapes both immediate behavioral responses and attitudes that can influence employees' performance in the long term. The second level focuses on individual differences, as an individual's specific characteristics determine the frequency, intensity, and duration of emotional experiences. Individual aspects such as emotional intelligence, organizational commitment, trait affectivity, and job satisfaction are particularly influential at this level. The third level explores the role of emotions in interpersonal relationships, and particularly dyadic interactions. Emotions are said to shape communication, which often occurs through the recognition of emotional cues such as tone of voice and facial expressions, with cascading effects on organizational dynamics. The fourth level addresses group and leadership dynamics, emphasizing constructs such as group affective tone and emotional contagion. The fifth level concerns the organization as a whole, focusing on constructs such as emotional climate, in order to analyse group phenomena that can be clearly perceived. Ashkanasy's model provides an explanation of how emotions impact the organizational level (Ashkanasy and Dorris, 2017). Numerous empirical studies have substantiated the impact of emotions on job crafting (Rogala and Cieslak, 2019; Griep et al., 2022; Barclay et al., 2022), self-efficacy (Heuven et al., 2006; Loeb et al., 2016), change (Vakola and Petrou, 2018), and the overall workplace experience (Elfenbein, 2023).

The role of positive emotions in shaping organizational behavior (Seligman and Csikszentmihalyi, 2014; Diener and Seligman, 2018) has also been highlighted by other theoretical frameworks, including positive psychology. Emerging as a response to approaches that predominantly focus on individual pathology and the negative aspects of one's being, positive psychology aims at emphasizing the personal resources that foster development and wellbeing (Xanthopoulou et al., 2007a; Argentero and Cortese, 2016). Therefore, the focus shifts on the factors that make life worth living (Seligman and Csikszentmihalyi, 2014; Alessandri et al., 2015b; Seligman, 2004), in an attempt to advance the study and application of “the strong points and positively oriented psychological abilities which can be effectively measured, developed and managed to improve performance in the current work contexts” (Luthans, 2002). Different studies have shown how the development of positive aspects, such as emotions, has a direct impact on organizational performance, commitment, and overall wellbeing (Di Fabio, 2017; Ingusci et al., 2019; Alessandri et al., 2015b; Boon et al., 2011; Alessandri et al., 2015a).

As research in positive psychology has demonstrated, individual strengths also include the attitude adopted when dealing with problems, with a focus on positive emotions. In this regard, studies by Lee (2021) and Lyu et al. (2021) have revealed that the positive functioning of individual workers, based on their experiencing positive emotions, can serve as a protective factor against adverse outcomes, such as post-traumatic stress disorder. It has also been shown that such emotions can be fostered through adequate organizational support, which may influence the psychological climate of the organization.

Accordingly, a second hypothesis was formulated:

H2: Personal resources, such as positive emotions, positively impact strategies to cope with organizational change.

2.3 Strategies to cope with organizational change

Within the current historical, social, and economic context, workers are increasingly required to respond to various forms of organizational change—alterations to existing routines and strategies of an organization (Herold et al., 2008). Reactions to such disruptions are subjective and generally depend on several factors. For instance, the either positive or negative perception of change impacts the way change itself is addressed or managed. Change that is perceived as stressful triggers defense mechanisms, whereas change that is perceived as motivational makes professionals more willing to embrace it. As an organization is a complex system consisting of different relationships and subjective experiences, change requires the active involvement of two key actors: managers and employees.

It has been proven that either significant or minor changes to the status quo inevitably give rise to new uncertainties. The way in which these new circumstances are addressed is generally described as coping. According to Folkman et al. (1986), coping involves the “cognitive and behavioral efforts of the individual in managing (reducing, minimizing or tolerating) internal requests and external requests of the person-environment transaction, which is viewed as imposing or superior to the resources of the person” (p. 572). In the literature, coping strategies have been categorized as either problem-focused or emotion-focused. While the former aim at directly addressing the source of stress, the latter involve dealing with the emotional responses caused by stressors (Folkman et al., 1986; Callan, 1993).

Different studies have revealed that major changes often act as stressors, leading to negative outcomes such as job loss, increased work-life conflict, and reduced psychological wellbeing (Ashford, 1988; Schweiger and Denisi, 1991). Dispositional, situational, and organizational factors influence the tendency to cope with change. Dispositional factors include personality traits that distinguish individuals from one another. Research has identified several traits that can positively influence change management, including locus of control, openness to experience, and tolerance for ambiguity (Fugate et al., 2008). Situational factors refer to the specific characteristics of a given context of change. These include the frequency of change, the planning of the structural elements connected with it, and the impact of change on the existing situation (Rafferty and Griffin, 2006). Organizational factors pertain to the indirect support system that companies provide to help employees to embrace change. These may include positive employee-manager relationships (Manuti et al., 2020; Parish et al., 2008), effective leadership practices (Herold et al., 2008; Manuti et al., 2020; Shum et al., 2008; Michaelis et al., 2010), adequate technologies and infrastructures to support change (Manuti et al., 2020; Michaelis et al., 2010), satisfaction with human resource practices (Manuti et al., 2020; Conway and Monks, 2008), participation in the process of change and perception of some of its characteristics, such as equity (Manuti et al., 2020; Devos et al., 2007; Bernerth et al., 2007), effective information (Manuti et al., 2020; Michaelis et al., 2010), and procedural and informational justice (Manuti et al., 2020; Michaelis et al., 2010).

Finally, various studies have highlighted how certain aspects of an individual's personal resources can positively influence their attitude toward organizational change. Job crafting has been identified as one of such factors (Petrou et al., 2015, 2018). Research (Petrou et al., 2015, 2018) has also shown that job crafting serves as an effective proactive response to organizational change, improving employee engagement, wellbeing, and adaptability.

During the COVID-19 pandemic, the work environment was characterized by significant imbalances between job demands (e.g., workload, emotional labor, digital stress) and available resources (e.g., autonomy, social support). According to the Job Demands-Resources model (Bakker and Demerouti, 2017), an excess of job demands, combined with a shortage of resources, can compromise psychological wellbeing and job performance, leading to phenomena such as chronic stress, burnout, and disengagement. In these critical contexts, job crafting serves as a proactive adaptive strategy, as it allows workers to actively modify the content or context of their work in order to re-establish a more functional balance between demands and resources. In practice, employees may increase structural resources by learning new skills or seeking new challenges, taking novel initiatives or creatively redefining their role. They may reduce hindering demands by avoiding emotionally challenging situations or better planning their activities to prevent overload. Recent empirical evidence supports this mechanism. Some studies (Zampetakis, 2021) have shown that job crafting served as a coping strategy for COVID-related fear, while others (Pijpker et al., 2022) have demonstrated its protective effect against burnout. Research by Ingusci et al. (2021) has further confirmed its role in mitigating behavioral stress caused by technostress.

Studies by Vakola and Petrou (2018) and Liu and Perrewé (2005) have shown that experiencing positive emotions can significantly impact the management of organizational change. Finally, self-efficacy also seems to positively influence an individual's attitude toward organizational change, as suggested in research by Eliyana et al. (2016) and Fatima et al. (2020).

The construct of coping with organizational change was particularly explored during the COVID-19 pandemic, as job environments underwent major transformations, often without proper warning. Several studies have investigated factors that facilitated a smoother transition to the new reality brought about by the pandemic. More specifically, research by Yue (2021) has found that transparent communication within organizations was crucial, while emphasizing the importance of leadership characteristics and organizational identification. Finally, studies by Buonocore et al. (2023) and Chen and Tang (2022) have identified job crafting as a potential tool for managing frequent organizational changes, such as changes in management.

Based on the literature reviewed, a third hypothesis was formulated:

H3: Personal resources, such as self-efficacy, positively impact strategies to cope with organizational change.

2.4 Same conditions, same behavior: the role of age

As it has already been pointed out, this study focuses on the pandemic period, which impacted the work environment in diverse and significant ways, as widely confirmed by previous research (Barouki et al., 2021). Although previous studies have shown that age can influence work-related variables such as job crafting (Tims et al., 2013), positive emotions (Carstensen et al., 2003), and self-efficacy (Kanfer and Ackerman, 2004), the pandemic may have constituted a unique “strong situation” (Beckmann and Heckhausen, 2018; Ingusci, 2018) in which extreme environmental pressures override individual differences.

Marked by universal work disruptions, abrupt role changes, and widespread uncertainty, the COVID-19 crisis was expected to reduce typical age-related differences in coping, job crafting, and resource activation. This assumption finds support in the emerging literature on the COVID-19 pandemic, which shows that large-scale universal stressors may moderate traditional age-related differences in coping and work behaviors. For instance, Kim and Crimmins (2020) have reported that during the pandemic, age-related patterns in coping strategies became less distinct, as younger adults focused on resource availability, while older adults concentrated on the severity of the situation. Similarly, in a brief review, Bellotti et al. (2021) have argued that the widespread work disruptions caused by the pandemic led to converging experiences across different age groups.

These findings suggest that under constraining conditions, such as a global health emergency, age-related differences in coping and resource activation may be reduced, as individuals face similar pressing demands, regardless of their age. Although some studies have pointed to generational differences in responses to the pandemic, empirical evidence remains inconclusive and does not consistently support a significant effect of age on individual resources and proactive behaviors in the workplace.

For this reason, age is treated as a control variable in this study, with the aim of exploring its association with key constructs in the context of sudden organizational change. This approach encourages reflection on potential effects related to career stage, without positing strong theoretical assumptions or directional hypotheses. Age-related results are therefore discussed in descriptive and exploratory terms, in order to offer insights for future research on the role of age in organizational adaptation processes during times of crisis or transformation.

The Job Demands-Resources model serves as the reference framework for this study. The structural hypotheses formulated are visually presented in Figure 1.

Figure 1

Figure 1. The structural model with the hypothesized relationships. ^*p < 0.05, ^**p < 0.01, ^**p < 0.001.

3 Materials and methods

The investigation was conducted using Partial Least Squares Structural Equation Modeling (PLS-SEM), a non-parametric alternative to Covariance Based Structural Equation Modeling (CB-SEM). Well-suited for small sample sizes and complex models, PLS-SEM does not require that the data meet certain distributional assumptions (Cassel et al., 1999). By contrast, CB-SEM relies on maximum likelihood estimation and requires normally distributed data. Furthermore, PLS-SEM can easily manage reflective and formative measurement models (Ciavolino et al., 2022), as well as constructs measured by a single item, with no issues related to model identification. Compared to CB-SEM, PLS-SEM has stronger statistical power, which increases the likelihood of correctly identifying significant relationships that are truly present within a given population.

The choice of PLS-SEM was guided by both methodological and substantive considerations. As it has been pointed out in some studies (Hair et al., 2019; Sarstedt et al., 2022), PLS-SEM is particularly appropriate when the main objectives are prediction and theory development, as it prioritizes maximizing the explained variance of endogenous constructs. Despite the large sample size, the adoption of PLS-SEM was preferred to CB-SEM due to the complexity of the structural model, the presence of reflective constructs with few indicators, and the use of single-item latent variables (e.g., age). Although CB-SEM provides robust estimators for non-normal data, preliminary analyses indicated slight deviations from normality. In such cases, the non-parametric nature of PLS-SEM ensures more stable and reliable estimations (Hair et al., 2019; Henseler et al., 2009).

In line with recent methodological reflections, it is acknowledged that the use of PLS-SEM in this study was not strictly dictated by technical necessity, although it was chosen for its flexibility in modeling mediational relationships in emerging contexts. While certain features of the model favor the use of PLS-SEM, the overall structure is theoretically grounded, involves a limited number of reflective constructs, and is based on a large sample—conditions under which the use of CB-SEM with robust estimators could have also yielded satisfactory, or possibly better, results. Therefore, future research may explore the replicability and robustness of the findings using alternative analytical approaches.

3.1 Participants

Involving 782 working participants, this study was conducted at the height of the pandemic, between May and July 2020. A non-probabilistic, convenience sampling strategy was used. Participants were recruited by forwarding the questionnaire to a wide range of workers and encouraging them to share the link to the questionnaire with their colleagues. No exclusion criteria were applied. The only requirement was that participants were employed at the time of data collection.

Mean substitution was applied to handle missing data. According to a study by Lodder (2014), these missing values were considered non-response items—cases in which only part of the data in a unit is missing. Specifically, 3% of responses contained non-response items. Research by Tsikriktsis (2005) suggests that mean substitution is acceptable when missing data constitute < 10%. Comparative analyses between cases with and without missing data revealed no significant differences in demographic characteristics or key study variables, supporting the assumption that data were Missing Completely at Random (MCAR). Following established methodological recommendations (Little and Rubin, 2019; Graham, 2009), missing values were replaced using mean substitution, an acceptable procedure under MCAR conditions.

The questionnaire was administered online via Google Forms. Participants were informed of the main characteristics of the research and were free to decline to participate or withdraw at any time. Informed consent was obtained upon survey completion. All data were collected anonymously and processed in aggregate form. The questionnaire was created and distributed by Italian researchers. However, due to the nature of the sampling and the absence of a question on nationality, it was not possible to determine precise national demographics.

The mean age of the participants was 38.5 years (SD = 11.3), with respondents ranging from 17 to 70 years. In terms of gender, 59% (n = 461) of respondents were women, 40.8% (n = 319) were men, and 0.3% (n = 2) identified as non-binary. Most respondents (74.7%, n = 581) were in committed relationships, while 21.9% (n = 171) were single. About 58.2% (n = 455) of participants reported having no children, whereas 41.8% (n = 327) stated they were parents. As for educational background, 39.3% (n = 307) of respondents held a high school diploma, 27.1% (n = 212) a four-year degree, and 12% (n = 93) a three-year degree. Regarding employment type, 52.6% of participants (n = 411) had a permanent contract, 20.9% (n = 163) had a temporary contract, and 20.1% (n = 157) were self-employed or had a VAT number. Most respondents (52.4%, n = 410) worked in the private sector, 33.2% (n = 260) were employed in public bodies, 8.7% (n = 68) worked for private social services providers, such as associations and cooperatives, and 5.6% (n = 44) were employed by multiple organizations. At the time of data collection, 47.1% (n = 368) of participants were working remotely, while 16.6% (n = 130) were alternating between working from home and working in the office. A summary of the participants' demographic characteristics is shown in Table 1.

Table 1

Table 1. Participant demographics.

Through an in-depth analysis of the participants' job titles, the occupational composition of the sample was further specified. A prevalence of clerical and technical staff was identified, followed by operational and manual workers, including factory workers and firefighters. The sample also included smaller groups of individuals in customer service and sales, the military and protective services, as well as people in executive and managerial roles, entrepreneurs, and freelancers. Academic and research roles were also represented, with research fellows being included in the sample. This distribution shows that, while most individuals in the sample were employed in technical, administrative, and operational roles, a significant proportion of respondents came from executive, self-employed, academic, and public service sectors. This occupational diversity reflects a heterogeneous sample, enhancing the generalisability of the findings across various professional and organizational contexts.

Participants were employed across a wide range of sectors, which offered a varied view of the workforce. The most represented sector was that of professional services, including consulting, legal and accounting activities, which accounted for 18.2% of the sample. This was followed by both healthcare and public administration and tertiary services, each representing 15.2% of participants. Education also featured prominently, involving 9.1% of respondents. Additional sectors with equal representation—each accounting for 6.1% of the sample—included the primary sector (agriculture, fishing, and mining), construction and transport, commerce and retail, security and defense, and manufacturing. Smaller proportions were observed in food and catering services (3.0%), tourism and hospitality (3.0%), craftsmanship (3.0%), and telecommunications (3.0%). These data confirm the professional heterogeneity of the sample, with strong representation in sectors typically associated with knowledge-based, educational, and essential services.

3.2 Measurements

Each question, and hence the scales used, made specific reference to the pandemic period the workers were experiencing. When the questionnaire was administered, respondents were instructed to contextualize their answers to that period, in order to elicit the role of the investigated constructs during the pandemic. Therefore, responses were expected to clearly pertain to the pandemic context. The variables considered were measured using questionnaires validated in the literature and excellent reliability indices. More specifically:

• Job crafting: increasing structural resources and increasing challenging demands were measured using the Italian short scale of job crafting (Ingusci et al., 2018), with six items—three per each dimension. The increase in social resources was not investigated, as few categories of workers could work in groups during the pandemic. Therefore, this study focused exclusively on the dimensions of increasing challenging demands and increasing structural resources. Although social interactions were not entirely absent during the COVID-19 pandemic, physical distancing measures, remote working, and social restrictions considerably reduced opportunities for crafting social resources. Consequently, focusing on the task-related and structural aspects of job crafting was deemed more consistent with the actual possibilities available to employees during the period investigated (Petrou and Xanthopoulou, 2021; Rogala and Cieslak, 2019). The scale demonstrated good reliability, with Cronbach's α of 0.89 and McDonald's ω of 0.90. Example items for each dimension include: “I try to perfect my competences” and “When there is not much to do, I take that as a good opportunity to start new projects.”

• Positive emotions: as research by Warr (1990) suggested, this scale measures specific emotions such as calm, contentment, enthusiasm, optimism, and relaxation. Cronbach's α and McDonald's ω for the six-item scale were 0.86 and 0.87, respectively.

• Strategies to cope with organizational change: this construct was measured using three items from Judge et al. (1999). Cronbach's α was 0.70, while McDonald's ω was 0.71. An example item is: “Deep changes improve the company”.

• Self-efficacy: this construct was measured using the three-item approach adopted by Alessandri et al. (2015b), with Cronbach's α of 0.78 and McDonald's ω of 0.79. An example item is: “When I analyse a problem, I trust that I will find a solution.”

For all the scales, response options were provided on a 5-point Likert scale, where 1 corresponds to “completely disagree” and 5 corresponds to “completely agree.”

4 Results

The correlation matrix highlighted positive and significant bi-univocal associations between all the variables involved, except for age, as shown in Table 2.

Table 2

Table 2. Correlation matrix of included variables.

The results of the measuring and structural model were validated using 5,000 bootstrap resampling, which allowed for the assessment of confidence intervals and their significance. As for the measurement model, all the latent constructs demonstrated excellent and meaningful loadings. Specifically, job crafting loadings ranged from 0.75 to 0.85, coping with organizational change from 0.77 to 0.80, positive emotions from 0.66 to 0.86, and self-efficacy from 0.79 to 0.87. In terms of convergent validity, all the latent variables were explained by their individual indicators (AVE_COPING = 62.0%, AVE_{POS EMO} = 59.8%, AVE_{JOB CRAF} = 66%, and AVE_{SELF − EFF} = 70.0%) with average variance extracted values above 50%, as reported in Table 3.

Table 3

Table 3. Composite reliability indices assessing the internal consistency of latent constructs.

Discriminant validity was supported, as the Heterotrait-Monotrait index values were below 0.90 (Wijngaards et al., 2022; Carmona-Halty et al., 2021; Hair Jr et al., 2017), as shown in Table 4.

Table 4

Table 4. Heterotrait-Monotrait ratio of correlations for latent variables included in the model.

The measurement model highlighted that the job crafting construct has beneficial effects on positive emotions, as a high level of proactive behavior is associated with increased positive emotions [β = 0.38 (0.32; 0.45), p < 0.000] and self-efficacy [β = 0.45 (0.37; 0.52), p < 0.000]. This relationship reflects an enhanced sense of control over one's actions and a greater use of strategies to cope with organizational change. Consequently, an increase in proactive behavior leads to a higher likelihood of perceiving change as positive and manageable [β = 0.23 (0.15; 0.30), p < 0.000]. Hypothesis H1 was thus confirmed. Hypotheses H2 and H3 were also supported, as positive emotions [β = 0.20 (0.13; 0.26), p < 0.000] and self-efficacy [β = 0.25 (0.17; 0.34), p < 0.000] have a positive impact on change management, acting as partial mediators in the relationship between job crafting and coping with organizational change.

To formally assess the hypothesized mediation effects (H2 and H3), mediation analyses were conducted following the guidelines suggested in a study by Zhao et al. (2010). It was tested whether positive emotions and self-efficacy mediated the relationship between job crafting and coping with organizational change. The indirect effect of job crafting on coping through positive emotions was statistically significant (β = 0.08, p < 0.001), indicating that individuals who engaged more in job crafting reported higher levels of positive emotions, which in turn facilitated coping with change. Similarly, the indirect effect of job crafting on coping through self-efficacy was significant (β = 0.12, p < 0.001), suggesting that job crafting behaviors enhance individuals' beliefs in their capabilities, thereby promoting more effective coping strategies.

Both indirect effects were estimated using bootstrapping procedures with 5,000 resamples, ensuring robust inference. Confidence intervals did not include zero, further confirming the significance of the mediation paths. These findings support the theoretical assumptions underlying the model, highlighting the role of positive personal resources—positive emotions and self-efficacy—as mechanisms through which proactive work behaviors (i.e., job crafting) foster successful adaptation to organizational change, even in contexts characterized by high uncertainty such as the COVID-19 pandemic. The model, with appropriate coefficients, is represented in Figure 2.

Figure 2

Figure 2. The hypothesized model of the job crafting role during the pandemic with relevant coefficients.

The effect of job crafting on coping with organizational change was mediated by positive emotions (~9%) and self-efficacy (32.8%). Results showed that, during the pandemic, age had no significant effects on job crafting behaviors [β = 0.00 (−0.06; 0.10), p = 0.947], positive emotions [β = −0.03 (−0.07; 0.03), p = 0.205], or perceived self-efficacy [β = 0.00 (−0.03; 0.15, p = 0.936)]. To provide a more comprehensive understanding of the mediated paths and the magnitude of effects within the model, direct effects, specific indirect effects, total indirect effects, and overall total effects were calculated and reported alongside 95% bootstrap confidence intervals, both standard and bias-corrected.

The results highlighted that direct effects were significant and consistent, particularly for the paths between the core variables of the model. Specifically, job crafting significantly predicted coping (β = 0.19; 95% CI: 0.15; 0.24), as did self-efficacy (β = 0.56) and positive emotions (β = 0.46). By contrast, the direct pathways from age to coping, positive emotions, and self-efficacy were weak or non-significant, with confidence intervals including zero.

As for specific indirect effects, two main mediated paths emerged as particularly significant. The first pathway linked job crafting to coping via self-efficacy (β = 0.11; 95% CI: 0.07; 0.20), while the second linked job crafting to coping via positive emotions (β = 0.08; 95% CI: 0.05–0.11). Both were statistically significant, highlighting the importance of personal and affective resources as mediators. Conversely, specific indirect paths involving age as an independent variable were weak or null, with confidence intervals including zero. This supported a decrease in age-related differences under strong situational constraints, such as those imposed by the pandemic.

Total indirect effects reflected similar patterns. Job crafting showed a significant total indirect effect on coping (β = 0.19; 95% CI: 0.15; 0.24), confirming the relevance of the mediated paths. By contrast, the total indirect effects of age remained marginal or non-significant.

Finally, total effects (i.e., the sum of direct and indirect effects) reinforced the overall interpretive framework. Job crafting had a particularly robust total effect on coping (β = 0.42; 95% CI: 0.35; 0.48), followed by self-efficacy (β = 0.25; 95% CI: 0.17; 0.34) and positive emotions (β = 0.20; 95% CI: 0.13; 0.26). In contrast, the total effect of age on coping was weak and non-significant (β = −0.00; 95% CI: −0.02; 0.08).

Overall, these findings confirm the central role of job crafting, self-efficacy, and positive emotions as both direct and indirect predictors of coping strategies. Despite being exploratory and unanticipated, these results offer a starting point for reflection and theoretical discussion, suggesting that the pandemic—as a constraining context—may have contributed to reducing age-related differences.

In addition to the significance of the path coefficients, effect sizes (f²) were assessed for the significant relationships, in order to determine their practical relevance (Hair et al., 2019; Cohen, 1988). The findings revealed that the effect of job crafting on positive emotions was of medium magnitude (f² = 0.18), while its effect on self-efficacy ranged from medium to large (f² = 0.26), highlighting the crucial role of proactive behavior in enhancing key personal resources. The effects of self-efficacy (f² = 0.08) and positive emotions (f² = 0.05) on coping were small, suggesting that although these resources positively influence adaptation to change, their individual contributions are limited in magnitude. Similarly, the direct effect of job crafting on coping also showed a small effect size (f² = 0.06), supporting the idea that job crafting influences coping both directly and indirectly, chiefly through the enhancement of personal resources.

5 Discussion

This study highlighted how, during the pandemic and the consequent transformation of social and organizational dynamics, job crafting proved to be a powerful tool to activate personal resources and positive emotions, directly influencing individuals' propensity to embrace change positively. It also explored whether personal resources and positive emotions played a mediating role in coping with change, and whether age impacted self-efficacy, positive emotions, and job crafting under the extraordinary circumstances of a health emergency. The findings support the theoretical framework of the Job Demands-Resources model (Bakker and Demerouti, 2017; Bakker et al., 2023), confirming that proactive strategies such as job crafting play a central role in rebalancing demands and resources, even in critical circumstances such as those of a global health emergency.

As the hypotheses formulated were grounded in the assumptions of the JD-R model, this study extended its application to an unprecedented context of extreme uncertainty and widespread disruption. In this regard, the research should be understood as a theoretical effort to investigate whether JD-R mechanisms—such as job crafting—remain valid and operate adaptively in times of global crisis. The findings are also consistent with the framework of positive psychology (Seligman and Csikszentmihalyi, 2014; Salanova et al., 2013), which emphasizes how activating individual strengths and psychological capital fosters adaptation and wellbeing at work.

The results show the strategic importance that job crafting had for professionals during the emergency period. Originating as a strategy to adapt one's work to personal needs, job crafting is a transversal process that can be adopted by workers across all professions. It encompasses aspects that are common to all roles, including a cognitive component, which enhances the perceived meaning of one's work, a relational component, focused on the social aspect of one's job, and a task component, which involves adjustments to the scope of one's activities (Lodder, 2014).

Unlike top-down strategies driven by overarching structures such as Human Resources, job crafting is a bottom-up approach. It originates with the individual worker who, often through an unconscious process, seeks to enhance aspects such as autonomy, meaning, and emotional involvement. Engaging in behaviors aimed at subtly modifying professional boundaries and adapting work to personal needs have been shown to increase personal resources such as self-efficacy, while also fostering positive emotions such as optimism and hope.

Job crafting seems to have a direct impact on how individuals respond to change—a key process at a time when office-based work was no longer feasible due to public health concerns (Manuti et al., 2020). The mediating effect of positive emotions and self-efficacy, activated through job crafting, played a significant role in managing these transformations, creating favorable conditions for coping with the new normal.

It was found that age had no impact on job crafting, positive emotions, or self-efficacy. This result may be interpreted in light of the fact that the pandemic exposed all workers, regardless of age, to exceptional circumstances, prompting individual responses that were not age-dependent. These findings challenge previous assumptions that age influences resource activation (Ingusci et al., 2019; Tims et al., 2013; Carstensen et al., 2003), suggesting that, in extreme contexts, individual differences may be reduced, as universally shared adaptive mechanisms are triggered.

This also led to verifying the empirical validity of the job crafting construct as a factor that can promote change and wellbeing within organizations. More specifically, it was possible to identify how this proactive behavior contributes to influencing key outcomes related to work processes, by testing theoretically grounded relationships even in periods of significant social and professional disruption.

5.1 Conclusion and practical implications

This study is consistent with previous research that investigated how individual and job-related factors fostered resilience during the COVID-19 pandemic (Gavin et al., 2022; Carstensen et al., 2003; Lodder, 2014). Based on the Job Demands-Resources model—widely adopted to analyse protective strategies in organizational contexts (Shamsi et al., 2021; Bilotta et al., 2021)—the findings reinforce the idea of job crafting as a proactive and effective approach to manage crisis-induced disruptions. As highlighted in earlier studies (Pijpker et al., 2022; Månsson Sandberg et al., 2024; Zampetakis, 2023), job crafting seems to positively influence how individuals use their personal strengths as drivers of growth, an aspect that aligns with core principles of positive psychology (Seligman and Csikszentmihalyi, 2014; Tsikriktsis, 2005).

While a number of previous studies have emphasized the mediating or moderating role of job crafting (Robledo et al., 2019; Weber, 2019), this research has primarily aimed to test theoretically grounded hypotheses and explanatory mechanisms concerning the relationships between job crafting, personal resources, and coping strategies in a high-demand context. Although the connection between job crafting and self-efficacy has extensively been explored (Miraglia et al., 2017; Tims et al., 2014), fewer studies have examined its links to positive emotions and adaptive responses to organizational change. The findings of this study support the notion that job crafting fosters the development of individual resources—particularly self-efficacy and positive emotions—that mediate the relationship between proactive behaviors and change management.

These findings align with the assumption, based on the JD-R model, that individuals actively shape their work environment to maintain motivation and wellbeing, even under highly uncertain conditions. Drawing on Bandura's self-efficacy theory and Fredrickson's broaden-and-build theory, job crafting emerges as a strategy that strengthens competence beliefs and emotional resilience. This study also finds support in self-determination theory, which views such proactive behavior as a way to satisfy psychological needs for autonomy and competence. While grounded in a specific pandemic-related context, the findings yield insights that can inform concrete organizational practices, particularly in times of uncertainty or crisis.

One key implication concerns the role of Human Resources practices in facilitating job crafting. Organizations can promote job redesign opportunities by encouraging participative work design, supporting employee autonomy, and integrating structured reflection moments into daily activities. Leadership behavior also plays a central role in this context: transformational and empowering leadership styles may help to create psychologically safe environments where employees feel encouraged to proactively shape their tasks and roles. Moreover, fostering self-efficacy and positive emotions within organizational settings may be especially critical during periods of disruption. Training programmes aimed at enhancing personal coping resources, providing constructive feedback, and recognizing small achievements can contribute to building a sense of competence and emotional resilience.

In the context of remote work—which was widely adopted during the pandemic—managers should pay particular attention to maintaining relational connectedness, emotional support, and clarity of expectations to sustain motivation and engagement. These findings also offer guidance for developing crisis-responsive organizational policies. For instance, integrating psychological resource-building strategies into emergency preparedness plans can help to buffer the impact of future shocks.

Overall, while this study focuses on a pandemic-driven transformation, its implications are transferable to broader contexts characterized by volatility, such as technological disruptions and organizational restructuring. Future studies might further examine how specific interventions, such as job crafting workshops or resilience training, influence adaptive processes across diverse work environments.

Although this study offers some important contributions, certain limitations should be acknowledged. Firstly, the use of non-probabilistic convenience sampling limits the generalisability of the results and may introduce selection bias (Bornstein et al., 2013; Etikan et al., 2016). Secondly, reliance on self-report instruments increases susceptibility to common method bias and social desirability effects (Podsakoff et al., 2003). Even though procedural remedies were applied, no statistical controls for bias were conducted. Additionally, given the emergency context in which data were collected, some perceptions may have been amplified by the emotional climate of the pandemic.

From a methodological standpoint, the use of PLS-SEM allowed for flexibility in the analysis of complex relationships with a limited sample size (Hair et al., 2019; Hair Jr et al., 2017; Hair et al., 2006), despite providing only exploratory causal interpretations. Future research should replicate these findings using longitudinal and experimental designs to clarify the directionality and durability of the observed effects.

Furthermore, this study controlled only for age, in order to maintain a parsimonious model. Although age did not seem to significantly influence the outcomes, future studies should consider additional sociodemographic and occupational variables, such as job tenure and education, so as to gain a more comprehensive understanding of the phenomena. Including personality traits, such as optimism or baseline self-efficacy, could also help to rule out alternative explanations by identifying potential confounding variables.

In light of these theoretical and practical considerations, this study consolidates a multidimensional framework in which job crafting is understood as both a coping response and a developmental strategy that fosters personal resource acquisition and organizational adaptability (Cenciotti et al., 2016; de Devotto and Wechsler, 2019). Future research should further investigate these dynamics—especially through longitudinal, experimental, or qualitative methods—to explore the sustainability and contextual variations of job crafting interventions. Moreover, future studies should adopt a multilevel approach (Nielsen and Miraglia, 2017) to capture the interactions between individual and organizational factors influencing job crafting and change management. Within this framework, variables such as leadership style, perceived organizational support, and organizational justice may act as moderators or mediators in the relationships between job crafting, personal resources, and coping.

In conclusion, the findings of this study underscore the strategic potential of job crafting as a self-initiated behavior that can improve wellbeing and professional performance. Particularly in high-risk contexts such as health emergencies, job crafting may serve as a flexible and scalable intervention to support those most vulnerable to sudden professional, economic, and social changes (Ingusci et al., 2019; Petrou and Xanthopoulou, 2021; Van den Heuvel et al., 2015; Kooij et al., 2017).

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

Ethical review and approval was not required for the study onhuman participants in accordance with the local legislationand institutional requirements. The patients/participantsprovided their written informed consent to participate inthis study. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

Author contributions

FS: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Writing – original draft, Writing – review & editing. EI: Conceptualization, Investigation, Project administration, Resources, Supervision, Visualization, Writing – original draft, Writing – review & editing. ED: Data curation, Investigation, Resources, Writing – review & editing. AC: Conceptualization, Data curation, Resources, Writing – review & editing. CC: Investigation, Project administration, Supervision, Writing – review & editing. EC: Conceptualization, Data curation, Formal analysis, Resources, Software, Supervision, Writing – review & editing.

Funding

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

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declare that no Gen AI was used in the creation of this manuscript.

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Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/forgp.2025.1576289/full#supplementary-material

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