Introduction
In recent decades, the workplace has undergone a radical transformation, shifting away from the rigid hierarchies and mechanistic models that once defined traditional organizational life (Tegtmeier, Weber, Sommer, Tisch & Wischniewski, Reference Tegtmeier, Weber, Sommer, Tisch and Wischniewski2022). From Taylorism, which prioritized productivity above everything else and did not leave space to creativity, autonomy, or emotional expression, to the more recent quantum paradigm, organizational theory has evolved to account for increasing complexity, emotional interdependence, and the psychological well-being of workers (Zohar, Reference Zohar2022). In this context, attachment theory – originally conceived by John Bowlby (Bowlby, Reference Bowlby1969) to explain early child-caregiver relationships – has emerged as a powerful lens through which to understand adult relational dynamics in professional environments. The relevance of this theory in organizational contexts lies in its capacity to illuminate how individuals form, maintain, or avoid emotional bonds with colleagues, supervisors, and the organization itself (Ren, Topakas & Patterson, Reference Ren, Topakas and Patterson2024). Organizations today operate in highly volatile, uncertain, complex, and ambiguous environments (U. S. Army War College, 1998). These conditions, and their evolution into what some describe as BANI contexts, brittle, anxious, nonlinear, and incomprehensible (Bushuyev, Piliuhina & Chetin, Reference Bushuyev, Piliuhina and Chetin2023), demand not only structural adaptability but also emotional and relational resilience among employees and leaders. Leadership is increasingly viewed not simply as a function of technical expertise or strategic vision, but as a relational role grounded in trust, emotional security, and psychological availability (Haver, Akerjordet & Furunes, Reference Haver, Akerjordet and Furunes2013).
In such scenarios, attachment theory offers a compelling framework to understand how individuals perceive support, engage with workplace stressors, and build professional relationships (Sutil-Martín & Rajas, Reference Sutil-Martín, Rajas, Baños and Sutil2022). Recent developments in organizational neuroscience and psychological safety have also renewed interest in understanding how early attachment styles manifest in adult professional behavior (Harms, Reference Harms2011; Meredith, Merson & Strong, Reference Meredith, Merson and Strong2007). Internal working models, understood as mental schemas that organize memory and relational expectations, are shaped during formative life stages (Ammaniti, Van Ijzendoorn, Speranza & Tambelli, Reference Ammaniti, Van Ijzendoorn, Speranza and Tambelli2000; Zimmermann, Reference Zimmermann1999). They influence how individuals perceive, interpret, and respond to social experiences.
In organizational contexts, they continue to inform how employees assess trustworthiness, interpret intentions, and handle feedback or conflict (Collins & Allard, Reference Collins, Allard, Fletcher and Clark2001; Mikulincer & Shaver, Reference Mikulincer and Shaver2007). This makes attachment theory not only relevant for interpersonal relationships but central to understanding the emotional fabric of organizational life (Warnock, Ju & Katz, Reference Warnock, Ju and Katz2024). Securely attached individuals are more likely to thrive in collaborative and dynamic environments, while those with anxious or avoidant attachment patterns may struggle with ambiguity, change, or relational demands (Ren et al., Reference Ren, Topakas and Patterson2024).
Despite the growing recognition of the importance of attachment styles in the workplace, tools for measuring this construct in organizational settings remain limited, particularly in Spanish-speaking contexts (Warnock et al., Reference Warnock, Ju and Katz2024). While several attachment instruments exist, many have been designed for clinical or interpersonal domains and lack the contextual specificity required for workplace assessment. The adult attachment interview (George, Kaplan & Main, Reference George, Kaplan and Main1996), for instance, provides rich qualitative insights but is impractical for large-scale use. Self-report instruments such as the Experiences in Close Relationships scale (Brennan, Clark & Shaver, Reference Brennan, Clark and Shaver1998) or the Attachment Style Questionnaire (Feeney, Noller & Hanrahan, Reference Feeney, Noller, Hanrahan, Sperling and Berman1994) offer greater accessibility, yet they often overlook workplace-specific relational dynamics, such as those involving leadership hierarchies, role boundaries, and task interdependence.
In this light, the lack of validated instruments to measure workplace-specific attachment styles within the Spanish population represents a significant gap (Warnock et al., Reference Warnock, Ju and Katz2024). Cultural adaptation is essential, as attachment behaviors are also shaped by social norms, leadership expectations, and communication styles (Ren et al., Reference Ren, Topakas and Patterson2024). The present study seeks to fill this void by introducing and validating (Cook & Beckman, Reference Cook and Beckman2006) a 38-item instrument designed to assess secure, avoidant, and anxious-ambivalent attachment styles specifically within professional settings. By grounding the scale in Bowlby’s theoretical framework and tailoring its items to workplace dynamics, this research contributes to a more nuanced understanding of adult attachment as it plays out within modern organizational ecosystems.
This manuscript is organized into the following sections. Section 2 presents a review of the literature and develops the theoretical framework underpinning the study. Section 3 outlines the research methodology and describes the instruments used for data collection. Section 4 focuses on the analysis and validation of the proposed scale, employing both exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) techniques. Section 5 offers a discussion of the findings, along with a comparative overview of other available psychometric tools that, while relevant, have not been validated for the Spanish business population. Finally, Section 6 highlights the main conclusions of the study, considering its limitations, and outlines directions for future research.
Literature review
The shift in the business paradigm
Since the 17th century, scientific thinking has been dominated by the mechanistic paradigm, grounded in Newtonian laws that described a linear, deterministic, and predictable universe (Capra, Reference Capra1982). This vision, when transferred to the business world by Taylor (Reference Taylor1911), gave rise to Taylorism: an organizational model characterized by extreme division of labor, rigid hierarchies, employees viewed as interchangeable parts, and the leader as a strong, centralized authority figure. While this approach increased productivity, its impersonal nature, exclusive focus on output, and low adaptability have rendered it obsolete in today’s context (Burns & Stalker, Reference Burns and Stalker1961; Morgan, Reference Morgan1998).
The contemporary organizational environment is defined by volatility, uncertainty, complexity, and ambiguity, captured by the acronym volatile, uncertain, complex, and ambiguous (U.S. Army War College, 1998). This has resulted in a rapidly changing and unpredictable world in which organizations must be agile and highly adaptable to respond effectively to emerging conditions. Although the volatile, uncertain, complex, and ambiguous model accurately describes the current context, it has limitations in fully capturing its complexity. In response, the BANI model was proposed, standing for brittle, anxious, nonlinear, and incomprehensible (Cascio, Reference Cascio2020). This model introduces new dimensions such as perceived structural fragility, collective anxiety, and cognitive overload in the face of the incomprehensible, highlighting emotional and psychological impacts on individuals and organizations. While it is true that the emergence of artificial intelligence in organizational management has become a valuable tool for decision-making in uncertain environments, enhancing adaptive and predictive capacities (Saura & Bužinskienė, Reference Saura and Bužinskienė2025) and optimizing strategic processes (Bessa & Barbosa, Reference Bessa and Barbosa2025; Hernández-Tamurejo González-Padilla & Saiz-Sepúlveda, Reference Hernández-Tamurejo, González-Padilla and Saiz-Sepúlveda2025), the establishment of strong interpersonal relationships, understanding employees’ attachment styles at the workplace, and the development of high levels of socioemotional skills (Villena-Martínez, Rienda-Gómez, Sutil-Martín & García-Muiña, Reference Villena-Martínez, Rienda-Gómez, Sutil-Martín and García-Muiña2024) within the workplace remain essential for organizational well-being. As such, it calls for not only adaptive structures but also emotionally intelligent leadership (Sutil-Martín & Rajas, Reference Sutil-Martín, Rajas, Baños and Sutil2022).
The organizational quantum paradigm emerged as a response to the inability of traditional structures to adapt effectively to volatile environments. Inspired by principles of quantum physics, this paradigm views companies as living, complex, and interconnected systems (Zohar, Reference Zohar2022). It promotes self-organization, energy flow management, holistic thinking, and the development of human relationships as central pillars of business operations (Capra & Luisi, Reference Capra and Luisi2014). Instead of vertical hierarchies, bottom-up models like those implemented by Haier or Spotify are proposed, fostering autonomy, shared purpose, and adaptability (Zhang & Greeven, Reference Zhang and Greeven2020).
Under this paradigm, leaders transition from authoritarian figures to facilitators of human development, while employees assume greater responsibility and become co-creators of the organizational environment (Tegtmeier et al., Reference Tegtmeier, Weber, Sommer, Tisch and Wischniewski2022). However, despite redefining structure and philosophy, this paradigm does not provide tools to understand how mental, emotional, and motivational states are generated, sustained, or transformed in the workplace (Ren et al., Reference Ren, Topakas and Patterson2024). Organizational neuroscience offers a valuable complement by providing empirical insights into how brain activity underlies cognitive and affective processes that influence decision-making, relational dynamics, and organizational culture (Siegel, Reference Siegel2010). This discipline allows for the transformation of the systemic and energetic approach of the quantum paradigm into practical interventions based on understanding motivation, emotional self-regulation, and social connection (Rock & Ringleb, Reference Rock and Ringleb2009).
In organizations operating under the quantum paradigm, the flow of information, interpersonal relationships, and trust are as important as technical skills or processes (Wheatley, Reference Wheatley2006). In adults, these relationships are mediated by attachment style, which acts as a perceptual and emotional filter influencing how individuals build workplace relationships, interpret intentions, or negotiate boundaries (Davidovitz, Mikulincer, Shaver, Izsak & Popper, Reference Davidovitz, Mikulincer, Shaver, Izsak and Popper2007). This makes attachment a critical factor in environments that rely on emotionally secure interdependence.
Attachment and its types
Attachment theory, developed by John Bowlby (Bowlby, Reference Bowlby1969, Reference Bowlby1982), explains how early emotional bonds with caregivers form internal working models that guide relational behavior throughout life. These models operate automatically, integrating past emotional experiences to predict the availability of support, thereby influencing emotional regulation and perceptions of oneself and others (Ainsworth, Blehar, Waters & Wall, Reference Ainsworth, Blehar, Waters and Wall1978; Bowlby, Reference Bowlby1988). Attachment styles were classified into secure and insecure, with the latter divided into anxious and avoidant types.
Individuals who experience consistent and sensitive responses to their needs in childhood are likely to develop a secure attachment style, characterized by a positive view of self and others, a sense of being worthy of support, and seeing others as reliable providers of that support (Collins, Reference Collins1996). When a caregiver’s responses are inconsistent with the child’s needs, the child may develop two distinct types of internal working models, leading to an anxious, insecure attachment style, characterized by a negative self-view and doubts about being deserving of support, even if others are seen as capable of providing it (Ainsworth et al., Reference Ainsworth, Blehar, Waters and Wall1978). Conversely, in cases where attachment figures are perceived as repeatedly unavailable or absent, an avoidant attachment style may emerge, characterized by a positive self-view and belief in one’s worthiness of support, coupled with distrust in others’ ability to provide it (Richards & Schat, Reference Richards and Schat2011).
There are two main approaches to conceptualizing adult attachment: the categorical approach, which uses discrete typologies, and the dimensional approach, proposed by Bartholomew and Horowitz (Reference Bartholomew and Horowitz1991), which maps attachment on axes of anxiety and avoidance. Recent literature suggests that, although the dimensional model of attachment provides statistical sensitivity to capture individual gradients, offering greater precision in assessing individual differences, categorical approaches remain relevant in applied contexts. Meta-analyses (Warnock et al., Reference Warnock, Ju and Katz2024) have confirmed that categorical attachment styles show significant correlations with variables of interest in organizational settings, such as job performance, satisfaction, and burnout, as well as with personality traits described in the Big Five model (Mammadov, Reference Mammadov2022), thereby enhancing their validity. More recent studies (Morales-Vives, Ferre-Rey & Ferrando, Reference Morales-Vives, Ferre-Rey and Ferrando2025) demonstrate that through mixed-method analyses, valid categorical profiles can be identified within dimensional structures, supporting the utility and validity of the categorical approach to attachment for diagnostic purposes and practical applications in organizational contexts. For this reason, many studies, particularly applied ones, tend to favor the categorical approach.
Adult attachment becomes activated in emotionally significant situations such as intimacy, stress, or the search for support (Mikulincer & Shaver, Reference Mikulincer and Shaver2007), manifesting in emotional regulation patterns, coping styles, and modes of interpersonal bonding. Securely attached individuals tend to form relationships based on trust and mutual support, while insecure attachment styles are associated with anxiety, relational difficulties, and lower resilience (Mikulincer & Shaver, Reference Mikulincer and Shaver2005).
In organizational contexts, attachment style influences key variables such as leadership perception, conflict management, teamwork, and adaptability to change (Harms, Reference Harms2011; Richards & Schat, Reference Richards and Schat2011). Within the quantum paradigm, which emphasizes relationships and emotional energy in organizations, understanding attachment becomes essential for designing emotionally sustainable workplaces and developing appropriate assessment tools.
Attachment in the organizational context
The study of attachment in organizational settings extends Bowlby’s (Reference Bowlby1969) theory into adulthood, with recent research consolidating its application in the workplace. Yip, Ehrhardt, Black & Walker (Reference Yip, Ehrhardt, Black and Walker2018) and Warnock et al., (Reference Warnock, Ju and Katz2024) emphasize how internal working models formed early in life shape individuals’ relationships with authority figures and peers in professional environments, particularly in complex organizations where interpersonal dynamics are essential.
In organizational contexts, internal working models function as cognitive-emotional templates that guide how employees perceive, interpret, and respond to relational experiences at work. Rooted in early attachment relationships, these models influence how individuals view themselves and others in professional settings, shaping expectations of support, trust, and responsiveness (Ren et al., Reference Ren, Topakas and Patterson2024). Recent theoretical frameworks suggest that internal working models regulate workplace behavior through cognitive, affective, and behavioral self-regulation mechanisms, thereby impacting decision-making, collaboration, and emotional resilience (Ren et al., Reference Ren, Topakas and Patterson2024).
These models operate differently across relational domains; for instance, employees may hold distinct attachment representations toward supervisors versus peers, which in turn influence performance, communication patterns, and the sense of inclusion within teams (Vîrgă, Opre & Popescu, Reference Vîrgă, Opre and Popescu2023). Moreover, perceiving a leader as an attachment figure, someone who provides availability, support, and emotional security, has been shown to strengthen engagement and performance, although it may also heighten dependency-related anxiety under certain conditions (Lisá, Greškovičová & Krizova, Reference Lisá, Greškovičová and Krizova2021). Taken together, these findings underscore the profound role of internal working models in shaping organizational dynamics and highlight the importance of fostering secure, responsive leadership environments to enhance individual and collective functioning.
Adult attachment styles have been shown to predict motivation, job orientation, and work attitudes (Ren et al., Reference Ren, Topakas and Patterson2024). Anxious attachment is associated with emotional insecurity, low self-efficacy, and heightened rejection sensitivity, increasing perceived stress and the likelihood of burnout (Moriano, Molero, Laguía, Mikulincer & Shaver, Reference Moriano, Molero, Laguía, Mikulincer and Shaver2021). Conversely, avoidant attachment correlates with emotional suppression, excessive autonomy needs, and difficulties in forming trusting relationships, which also contribute to occupational stress (Ren et al., Reference Ren, Topakas and Patterson2024; Warnock et al., Reference Warnock, Ju and Katz2024).
Both insecure styles are negatively associated with job satisfaction and self-efficacy (Warnock et al., Reference Warnock, Ju and Katz2024), and they hinder the quality of relationships with supervisors. Anxiously attached individuals often fear criticism or a lack of empathy from superiors (Moriano et al., Reference Moriano, Molero, Laguía, Mikulincer and Shaver2021), while avoidant individuals tend to reject collaboration and behave overly independently (Kirrane, Yip, Ehrhardt & Walker, Reference Kirrane, Yip, Ehrhardt and Walker2019).
These patterns affect the quality of leader-member exchanges, limiting autonomy, trust, and mutual loyalty (Mayseless & Popper, Reference Mayseless and Popper2019). Insecure attachment styles also influence job performance and organizational citizenship behaviors, either through emotional interference in the case of anxious attachment or disengagement from collective responsibilities in the case of avoidant attachment (Warnock et al., Reference Warnock, Ju and Katz2024).
Recent studies have introduced the concept of organizational attachment, defined as the emotional bond between employees and the organization as a symbolic attachment figure. Organizations that function as a secure base, being available, consistent, and responsive, can foster innovation, resilience, and commitment among members (Mayseless & Popper, Reference Mayseless and Popper2019; Westover, Reference Westover2024). These findings highlight the explanatory power of attachment in organizational dynamics and underscore the need for context-specific assessment tools.
Review of adult attachment and workplace attachment measurement instruments
Research on adult attachment has produced a wide range of assessment tools, allowing exploration of the construct through both qualitative and quantitative approaches in clinical, personal, and organizational contexts. One of the earliest and most significant instruments is the adult attachment interview, developed by George et al. (Reference George, Kaplan and Main1996), which provides an in-depth evaluation of internal working models through narrative interviews. Despite its validity, the adult attachment interview is complex to administer and requires extensive training (Ravitz, Maunder, Hunter, Sthankiya & Lancee, Reference Ravitz, Maunder, Hunter, Sthankiya and Lancee2010).
Self-report measures have gained prominence due to their ease of use and efficiency in research. Among the most widely recognized are the Experiences in Close Relationships (Brennan et al., Reference Brennan, Clark and Shaver1998) and its revised version Experiences in Close Relationships-R (Fraley, Waller & Brennan, Reference Fraley, Waller and Brennan2000), both extensively validated and applied. Other relevant tools include the Relationship Questionnaire (Bartholomew & Horowitz, Reference Bartholomew and Horowitz1991), which allows rapid classification but has lower internal reliability, and the Attachment Style Questionnaire (Feeney et al., Reference Feeney, Noller, Hanrahan, Sperling and Berman1994), which measures emotional and cognitive dimensions such as the need for approval and discomfort with closeness, relevant in workplace settings.
In the organizational field, the Current Relationship Interview (Crowell & Owens, Reference Crowell and Owens1998), initially designed for romantic relationships, has been adapted to study workplace bonds and leadership styles. More recently, Scrima et al. (Scrima, Reference Scrima2020; Scrima, Di Carlo, Lorito & Palazzeschi, Reference Scrima, Di Carlo, Lorito and Palazzeschi2015) developed the Workplace Attachment Style Questionnaire, specifically designed to assess attachment styles in professional environments, evaluating both the intensity and quality of emotional bonds with one’s job. However, this instrument has not yet been validated for the Spanish population. Greškovičová and Lisá (Reference Greškovičová and Lisá2023) have validated an adapted version of Scrima et al. (Scrima, Reference Scrima2020) for the Slovakian population. De Andrade and Pedruzzi (Reference De Andrade and Pedruzzi2020) have validated a workforce attachment scale for Brazilians.
Despite methodological advances, there remains a lack of culturally adapted and context-specific instruments for assessing adult attachment in Spanish organizational settings. Therefore, this research aims to develop a valid, reliable, and contextually grounded tool to support rigorous analysis of attachment in organizations and to foster emotionally sustainable work environments.
Designing an attachment scale to workforce context. What to measure?
The items in the scale were designed to gather the following information regarding attachment styles in the workplace context. Employees with a secure attachment style tend to display balanced emotional regulation (SEG2), a strong sense of self-efficacy (SEG1), and the ability to establish trusting and cooperative relationships at work (SEG3 and SEG5). These individuals are generally comfortable with both autonomy and emotional closeness, enabling them to collaborate effectively while maintaining healthy interpersonal boundaries (SEG4 and SEG6) (Feeney & Noller, Reference Feeney and Noller1996). Their capacity to seek support when needed, coupled with a positive view of others, fosters constructive problem-solving and emotional resilience in stressful situations. Research has consistently shown that secure attachment in the workplace is linked to higher levels of trust, teamwork, and adaptability to change (Harms, Reference Harms2011; Richards & Schat, Reference Richards and Schat2011). Securely attached employees are also more likely to interpret feedback constructively and experience greater job satisfaction and engagement (Moriano et al., Reference Moriano, Molero, Laguía, Mikulincer and Shaver2021) (see Table 1).
Table 1. Attachment items to the workplace context
Source: Authors’ own work.
In contrast, individuals with insecure attachment styles, either avoidant or anxious, exhibit relational tendencies that can hinder collaboration and psychological well-being in organizational settings (Ren et al., Reference Ren, Topakas and Patterson2024). Avoidantly attached employees often maintain emotional distance from colleagues and supervisors, show low trust in others’ intentions, and tend to suppress emotional expression, especially under stress, withdraw in conflicts, and reduce social engagement, feeling alienated (Kirrane et al., Reference Kirrane, Yip, Ehrhardt and Walker2019; Yip et al., Reference Yip, Ehrhardt, Black and Walker2018). This detachment can lead to decreased participation in team processes and lower organizational commitment (EVIT2, EVIT5, EVIT6, EVIT8-EVIT13, EVIT16, EVIT17, and EVIT19). Conversely, anxiously attached individuals may demonstrate excessive sensitivity to perceived social exclusion, emotional dependency on coworkers or leaders, and difficulty maintaining personal boundaries. Their intense concern about acceptance and validation often leads to emotional exhaustion and heightened stress (Ren et al., Reference Ren, Topakas and Patterson2024; Vîrgă, Iliescu & Sava, Reference Vîrgă, Iliescu and Sava2019a). Both insecure styles have been associated with reduced satisfaction, impaired communication, and increased risk of burnout (Warnock et al., Reference Warnock, Ju and Katz2024; Westover, Reference Westover2024), underscoring the importance of identifying and addressing these patterns within the workplace (ANS_AMB1, ANS_AMB3, ANS_AMB5, ANS_AMB6. ANS_AMB8-ANS_AMB10, ANS_AMB12, and ANS_AMB13) (see Table 1).
Psychometric instruments: validation and reliability
Validity and reliability concern how we interpret the scores produced by psychometric instruments in educational research (Cook & Beckman, Reference Cook and Beckman2006). Most approaches to judging validity come from psychological and educational-assessment theory (Messick, Reference Messick1989). The Standards for Educational and Psychological Testing define validity as “the degree to which evidence and theory support the interpretations of test scores for the proposed uses of tests” (APA. American Educational Research Association, American Psychological Association, & National Council on Measurement in Education, 1999; Borsboom, Mellenbergh & van Heerden, Reference Borsboom, Mellenbergh and van Heerden2004). In other words, validity is not an inherent trait of a test itself but of the meaning we give its scores and the inferences we draw from them (Cook & Beckman, Reference Cook and Beckman2006). Messick (Reference Messick1989) describes five sources of validity evidence:
• Content: We compare the test’s content with the construct that it is meant to measure (APA. American Educational Research Association, American Psychological Association, & National Council on Measurement in Education, 1999).
• Response process: By examining what test-takers think and do while answering, we check whether their behavior matches the construct (APA. American Educational Research Association, American Psychological Association, & National Council on Measurement in Education, 1999).
• Internal structure: Tools such as reliability estimates and factor analysis tell us whether the items group together as expected (Floyd & Widaman, Reference Floyd and Widaman1995; Sellbom & Tellegen, Reference Sellbom and Tellegen2019; Shrestha, Reference Shrestha2021).
• Relations to other variables: Scores should relate in predictable ways to scores from established instruments that assess similar constructs.
• Consequences: We evaluate the intended and unintended effects of using the test, looking for any sources of invalidity (Abeele, Spiel, Nacke, Johnson & Gerling, Reference Abeele, Spiel, Nacke, Johnson and Gerling2020).
Reliability is essential, though on its own it does not guarantee validity (Sürücü & Maslakci, Reference Sürücü and Maslakci2020). Reliability describes how consistently an instrument produces scores across occasions (APA. American Educational Research Association, American Psychological Association, & National Council on Measurement in Education, 1999). Without consistent scores, meaningful interpretation is impossible (Cook & Beckman, Reference Cook and Beckman2006). Common reliability estimates include internal consistency, measured by Cronbach’s alpha (Cronbach, Reference Cronbach1951); inter-rater agreement, measured by phi coefficient, weighted kappa, and Kendall’s tau (Nunnally & Bernstein, Reference Nunnally and Bernstein1994); and test–retest stability for scores over time (Noble, Scheinost & Constable, Reference Noble, Scheinost and Constable2021).
High internal consistency suggests the items tap a single construct; low consistency signals that more than one construct may be involved (Cook & Beckman, Reference Cook and Beckman2006). For practical examples of scale validation, see Villena-Martínez et al. (Reference Villena-Martínez, Rienda-Gómez, Sutil-Martín and García-Muiña2024); Zurita Ortega, Martinez Martinez, Chacon Cuberos and Ubago Jiménez (Reference Zurita Ortega, Martinez Martinez, Chacon Cuberos and Ubago Jiménez2019); Moguerza, Fernández-Muñoz, Redchuk, Cardone-Riportella and Navarro-Pardo (Reference Moguerza, Fernández-Muñoz, Redchuk, Cardone-Riportella and Navarro-Pardo2017) and Moret- Tatay et al. (Moret-Tatay, Fernández Muñoz, Civera Mollá, Navarro-Pardo & Alcover de la Hera, Reference Moret-Tatay, Fernández Muñoz, Civera Mollá, Navarro-Pardo and Alcover de la Hera2015).
Methodology and instruments
The questionnaire is based on Bowlby’s theory, adapted by the authors to the workplace context. It considers two types of attachment: secure attachment and insecure attachment. Moreover, within the broader category of insecure attachment, two distinct subtypes can be identified: insecure avoidant and anxious-ambivalent attachment, as applied to organizational settings (Feeney & Noller, Reference Feeney and Noller1996). In this context, attachment refers to the emotional and relational bonds individuals develop with their coworkers, supervisors, and organizational leaders, drawing from Bowlby’s theoretical framework.
The questionnaire consists of 38 items, grouped according to the three different attachment styles mentioned above (Table 1). The first factor includes aspects related to secure attachment in the workplace. The second factor covers items that reflect patterns of insecure avoidant attachment. The third factor focuses on issues related to insecure anxious-ambivalent attachment.
All items were rated on a Likert scale from 1 to 6, where 1 means strongly disagree and 6 means strongly agree. The questions that show significance through the EFA for each attachment style are:
1. Secure attachment: SEG2, SEG3, SEG 4, and SEG6.
2. Insecure avoidant attachment: EVIT2, EVIT5, EVIT6, EVIT8, EVIT9, EVIT10, EVIT11, EVIT12, EVIT13, EVIT16, EVIT17, and EVIT19.
3. Insecure anxious-ambivalent attachment: ANS_AMB1, ANS_AMB3, ANS_AMB5, ANS_AMB6, ANS_AMB8, ANS_AMB9, ANS_AMB10, ANS_AMB12, and ANS_AMB13.
Experiment design
The data for the study were collected through non-probabilistic horizontal network sampling (Geddes, Parker & Scott, Reference Geddes, Parker and Scott2018), conducted via the social network LinkedIn. The sample targeted a population consisting of company executives, middle managers, and qualified professionals, who voluntarily completed an online questionnaire hosted on Microsoft Forms and accessed through a QR code. The questionnaire took approximately 15 minutes to complete.
It included screening questions to ensure that respondents were members of the target population. Additionally, it provided a link to an informed consent document outlining the study’s purpose and characteristics, along with clear instructions on how to withdraw from participation at any time. The study received approval from the institution’s Research Ethics Committee.
Participants
A total of 238 responses were obtained from professionals across various organizational levels. The respondents represented a wide range of industry sectors and company sizes, including small and medium-sized enterprises, family-owned businesses, and large corporations. Based on the screening questions, the data set was filtered, resulting in a final valid sample of 204 individuals. The adequacy of a sample size of approximately 200 participants for psychometric validation studies has been consistently addressed in methodological literature. Classical guidelines classify 200 cases as a “fair to good” sample size for factor analysis (Comrey & Lee, Reference Comrey and Lee1992), while simulation studies emphasize that adequacy depends more on model complexity, item communalities, and the magnitude of factor loadings than on absolute size alone (MacCallum, Widaman, Zhang & Hong, Reference MacCallum, Widaman, Zhang and Hong1999). In the context of structural equation modeling, Kline (Reference Kline2016) and Byrne (Reference Byrne2013), suggest that 200 cases are often considered the practical minimum for CFA, particularly when models are not excessively complex. Recent empirical research supports these methodological recommendations (Goni et al., Reference Goni, Naing, Hasan, Wan-Arfah, Deris, Nor Arifin and Njaka2020; Kiani, Pezeshkian, Bakhshandeh & Khakbazan, Reference Kiani, Pezeshkian, Bakhshandeh and Khakbazan2025; Sharif-Nia et al., Reference Sharif-Nia, Froelicher, Hoseinzadeh, Kaveh, Fatehi and Nowrozi2024). Consequently, a sample of 204 participants does not compromise the robustness of either the EFA or the CFA, as it falls within both classical and contemporary methodological criteria, maintains an adequate subject-to-item ratio, and allows for stable estimation of factorial parameters (Tables 2–5).
Table 2. Frequencies for gender
Source: Authors’ own work.
Table 3. Frequencies for Age_I
Source: Authors’ own work.
Table 4. Descriptive statistics for age
Source: Authors’ own work.
Table 5. Descriptive statistics
Source: Authors’ own work.
As shown in the tables above, 65.68% of the respondents were male and 34.31% were female. This finding suggests that leadership positions, middle management roles, and qualified professional occupations, such as lawyers, economists, and others, continue to be predominantly held by men rather than women (Table 2).
Regarding the variable Age (Tables 3 and 4), all age ranges are well represented, with the highest frequency corresponding to the 45–55 age group, which accounts for 30.39% of the sample. Descriptive statistics for the age variable indicate that the average age of participants is 41.13 years, with a standard deviation of 13.27 years. Measures of skewness show that the distribution is slightly skewed to the left, although the skewness value is not statistically significant; therefore, we can assume the variable is approximately symmetric.
Table 5 presents descriptive statistics for the items analyzed in this study. The mean values are approximately 4 points, indicating a general tendency among respondents to agree with the statements rather than to disagree. When focusing on the coefficient of variation, it can be observed that the mean serves as a representative measure of the frequency distribution. Table 6 and the subsequent tables present the frequency distributions of all items included in the study. For variables expressed as reverse-coded items, responses have been transformed to align with the overall response trend of the sample. Reverse-coded items were included to control for response bias. These items were recoded so that higher values consistently reflect greater agreement with the underlying construct (İlhan, Güler, Taşdelen Teker & Ergenekon, Reference İlhan, Güler, Taşdelen Teker and Ergenekon2024).
Table 6. Frequentist scale reliability statistics
Note: Of the observations, pairwise complete cases were used. The following items correlated negatively with the scale: SEG2, SEG3, SEG4, and SEG6.
Source: Authors’ own work.
Data analysis
Data were examined in JASP (v 0.17.2.1) by means of both exploratory (EFA) and CFA following Villena-Martínez et al. (Reference Villena-Martínez, Rienda-Gómez, Sutil-Martín and García-Muiña2024) and Moguerza et al. (Reference Moguerza, Fernández-Muñoz, Redchuk, Cardone-Riportella and Navarro-Pardo2017). Before running the EFA, multivariate normality, linearity, and inter-item correlation were inspected in line with the recommendations of Tabachnick and Fidell (Reference Tabachnick and Fidell1989). Factors were extracted with oblimin rotation; only components whose eigenvalues exceeded 1 were retained (Corner, Reference Corner2009). The dimensionality of the scale was gauged both through hypothesis-driven reasoning and Horn’s parallel analysis (Horn, Reference Horn1965; Lloret-Segura, Ferreres-Traver, Hernández-Baeza & Tomás-Marco, Reference Lloret-Segura, Ferreres-Traver, Hernández-Baeza and Tomás-Marco2014). Internal consistency was quantified with Cronbach’s α, item-total correlations, the Kaiser–Meyer–Olkin index, and Bartlett’s test of sphericity (Kaiser, Reference Kaiser1974). Missing data were handled using pairwise deletion, and outliers were inspected using standardized z-scores and Mahalanobis distance (Kline, Reference Kline2016). No extreme cases required exclusion. Normality and linearity assumptions were verified following Lloret-Segura et al. (Reference Lloret-Segura, Ferreres-Traver, Hernández-Baeza and Tomás-Marco2014).
Subsequently, CFA was conducted to verify the structure uncovered by the EFA and to appraise model fit. Several complementary indices were considered: the chi-square statistic (La Du & Tanaka, Reference La Du and Tanaka1989); the goodness-of-fit index, with 0.90 as the conventional lower bound for adequacy (Hu & Bentler, Reference Hu and Bentler1999); the root-mean-square residual, where values approaching 0 – particularly ≤0.08 – indicate better fit (Jöreskog & Sörbom, Reference Jöreskog and Sörbom1979); the Comparative Fit Index (CFI) and the Incremental Fit Index, both expected to reach at least 0.90 (Bentler, Reference Bentler1990); and, as a parsimony index, the root-mean-square error of approximation (RMSEA), for which lower values closer to 0 signal superior parsimony (Steiger, Reference Steiger2000). Average variance extracted, as a measure of convergent and discriminant validity, and the Heterotrait–Monotrait Ratio, as a measure of discriminant validity, were computed for CFA (Karakaya & Yıldırım, Reference Karakaya and Yıldırım2025; Kaynak, Tüzün & Demir, Reference Kaynak, Tüzün and Demir2021).
Exploratory factor analysis
Internal consistency
The proposed scale demonstrated strong internal consistency, with a Cronbach’s alpha coefficient of α = 0.939 and 
$\omega = 0.96$, compared to α = 0.83 reported by Scrima et al. (Reference Scrima, Di Carlo, Lorito and Palazzeschi2015) and α = 0.65 reported by (Hite & McDonald, Reference Hite and McDonald2020; Lisá & Mrázková, Reference Lisá, Mrázková, Pracana and Wang20212021) 
$\omega $ between 0.8 and 0.92 for Andrade and Pedruzzi (De Andrade & Pedruzzi, Reference De Andrade and Pedruzzi2020). The total variance explained by one factor analysis was 56.2% for secure attachment, 73% for insecure avoidant attachment, and 54.6% for insecure anxious-ambivalent attachment. Item-level analysis showed that Cronbach’s alpha remained stable between 0.953 and 0.964 across all cases when individual items were removed, suggesting no single item disproportionately influenced internal consistency (Tables 6 and 7).
Table 7. Frequentist individual item reliability statistics
Source: Authors’ own work.
To assess the equality of multivariate means, both Friedman’s ANOVA (Analysis of Variance) and Hotelling’s T 2 test were employed, revealing statistically significant differences (Carey, Sheehan, Healy, Knott & Kinsella, Reference Carey, Sheehan, Healy, Knott and Kinsella2022; Göktuna, Arslan & Özden, Reference Göktuna, Arslan and Özden2022). Descriptive statistics, as seen in Table 5, for each item, including measures of central tendency and dispersion, as well as skewness and kurtosis, were carried out. These indices were within acceptable limits, supporting the assumption of approximate normality. The distribution of item responses showed moderate symmetry. Regarding kurtosis, most items exhibited a leptokurtic pattern, indicating a higher-than-normal concentration of scores around the mean. This pattern suggests that participant responses were relatively consistent, clustering near central values rather than being widely dispersed.
To evaluate the suitability of conducting an EFA, Bartlett’s test of sphericity yielded a highly significant result (see tables below) and the Kaiser–Meyer–Olkin measure of sampling adequacy was greater than 0.82. As shown in Table 9, the p-value obtained from Bartlett’s test was well below the conventional alpha level of 0.05, confirming that the correlation matrix is appropriate for factor extraction. The high Kaiser–Meyer–Olkin value, exceeding the 0.75 threshold, further supports the adequacy of the data for factor analysis.
Following this verification, principal component analysis was performed. To allow for correlated latent constructs and improve factor interpretability, an oblimin rotation was applied (Luo, Arizmendi & Gates, Reference Luo, Arizmendi and Gates2019). The number of factors retained was determined based on the eigenvalue-greater-than-one criterion (Moguerza et al., Reference Moguerza, Fernández-Muñoz, Redchuk, Cardone-Riportella and Navarro-Pardo2017) and further substantiated through parallel analysis (Horn, Reference Horn1965), which helped identify the number of factors that explained a statistically meaningful portion of the variance.
The EFA has confirmed the existence of one main factor for each type of attachment, whose factor loadings are shown in the tables below, according to criteria set. The variables have been associated with each of the dimensions and factors according to the criterion of having the highest factor load in a significant way and not distributed among the rest of the dimensions. In those cases where the factor load could not be assigned a certain dimension, because it was shared between several factors, the item for the validation of the scale was not considered (Tables 8–18).
Table 8. Secure attachment
Source: Authors’ own work.
Table 9. Bartlett’s test
Source: Authors’ own work.
Table 10. Factor loadings (structure matrix)
Applied rotation method is oblimin.
Source: Authors’ own work.
Insecure avoidant attachment
Table 12. Insecure avoidant attachment
Source: Authors’ own work.
Table 13. Bartlett’s test
Source: Authors’ own work.
Table 14. Factor loadings (structure matrix)
Note: Applied rotation method is oblimin.
Source: Authors’ own work.
Table 15. Additional fit indices
Source: Authors’ own work.
Insecure anxious-ambivalent attachment
Table 16. Kaiser–Meyer–Olkin test
Source: Authors’ own work.
Table 17. Bartlett’s test
Source: Authors’ own work.
Table 18. Factor loadings (structure matrix)
Note: Applied rotation method is oblimin.
Source: Authors’ own work.
Table 19. Additional fit indices
Source: Authors’ own work.
Confirmatory factor analysis
In the context of CFA, incremental fit indices assess how well the proposed model improves upon a baseline or null model, typically one that assumes no relationships among observed variables (McNeish et al., Reference McNeish, An and Hancock2018; Jordan-Muiños, Reference Jordan-Muiños2021). Common indices in this category include the CFI, the goodness-of-fit index, and the Tucker–Lewis Index. A CFI value of 0.95 or higher is generally considered indicative of a well-fitting model (Lai, Reference Lai2021). For goodness-of-fit index, recommended cut-off values depend on sample size: values above 0.89 are acceptable for samples around 100 participants, while values above 0.93 are suggested for larger samples (Cho, Hwang, Sarstedt & Ringle, Reference Cho, Hwang, Sarstedt and Ringle2020). The Tucker–Lewis Index, likewise, should exceed 0.90 to reflect satisfactory model fit (Xia & Yang, Reference Xia and Yang2019).
Regarding absolute fit indices, the RMSEA provides an estimate of model fit adjusted for complexity. Values less than or equal to 0.06 suggest a good fit to the data (Lai, Reference Lai2021). The standardized root mean square residual is also widely used, with recommended thresholds of <0.09 for small samples (≤100) and < 0.08 for larger ones (Cho et al., Reference Cho, Hwang, Sarstedt and Ringle2020).
The chi-square statistic (χ2) remains a traditional measure of model fit. A statistically significant χ2 (p < .05) typically indicates poor fit; however, it is well documented that χ2 is highly sensitive to sample size (Walker & Smith, Reference Walker and Smith2017). Consequently, researchers often rely on the ratio of χ2 to degrees of freedom (χ2/df), with values below 3 generally considered acceptable (Wheaton, Muthen, Alwin & Summers, Reference Wheaton, Muthen, Alwin and Summers1977).
Notably, Rigdon (Reference Rigdon1996) emphasized conceptual limitations in the use of CFI, particularly its reliance on a baseline model, suggesting that CFI may be more suitable for exploratory contexts, whereas RMSEA is better aligned with confirmatory purposes. Furthermore, while CFI incorporates a parsimony adjustment, the correction embedded in RMSEA has been questioned for its adequacy. Thus, careful interpretation of model fit should involve multiple indices and consider sample size and theoretical grounding.
Model fit
Table 20. Chi-square test
Source: Authors’ own work.
Table 21. Fit indices
Source: Authors’ own work.
Table 22. Information criteria
Source: Authors’ own work.
Table 23. Other fit measures
Source: Authors’ own work.
Table 24. Kaiser–Meyer–Olkin (KMO) test
Source: Authors’ own work.
Table 25. Bartlett’s test of sphericity
Source: Authors’ own work.
Parameter estimates
Table 26. Factor loadings
Source: Authors’ own work.
As shown in Table 20, the goodness-of-fit indices associated with the EFA fall within the thresholds typically considered acceptable in the literature, indicating that the model provides an adequate representation of the underlying structure in the sample data.
Tables 22 and 23 present the results of the CFA, including several incremental fit indices. Most of the fit statistics, like CFI, chi-square, and RMSEA, fall within the recommended thresholds reported in previous studies. The χ2/df ratio (601.9/272 = 2.21) is below the commonly accepted cutoff of 3, indicating an acceptable model fit. Nonetheless, it is important to contextualize these findings: as Rigdon (Reference Rigdon1996) notes, RMSEA is generally regarded as a more reliable indicator of model adequacy in confirmatory contexts, particularly when contrasted with the CFI. Additionally, the chi-square statistics are known to be overly sensitive to large sample sizes, frequently leading to the rejection of acceptable models due to their tendency to detect trivial misfit (Wheaton et al., Reference Wheaton, Muthen, Alwin and Summers1977). Average variance extracted, as a measure of convergent and discriminant validity, and the Heterotrait–Monotrait Ratio, as a measure of discriminant validity, were computed for CFA, showing good values (
$AVE \geqslant 0.5\,and\,HTMT \leqslant 0.9)$ (Tables 28 and 29). Factor covariances show the appropriate correlation (Table 27).
Table 27. Factor covariances
Source: Authors’ own work.
Table 28. Average variance extracted
Source: Authors’ own work.
Table 29. Heterotrait–Monotrait ratio
Source: Authors’ own work.
Turning to the item-level parameter estimates (Table 26), all standardized loadings were positive and statistically significant. In most cases, the estimated parameters reached values of 1.0 or higher, suggesting that these items contribute substantially and positively to their respective latent dimensions.
Reliability
When examining the reliability of each construct individually, as assessed through both omega (ω) and Cronbach’s alpha coefficients, all factors exhibit reliability estimates within acceptable thresholds, as commonly cited in the literature. The overall reliability of the instrument is strong, with global indices falling well within recommended standards. This suggests that, at the scale level, the instrument performs reliably and aligns with psychometric expectations reported in prior research (see Tables 30 and 31).
Table 30. Reliability
Source: Authors’ own work.
Table 31. Frequentist individual item reliability statistics
Source: Authors’ own work.
Validity
To evaluate the internal validity of the proposed scale, procedures were implemented at the levels of content, criterion, and construct validity.
Content validity was established through expert review. The initial version of the instrument was submitted to a panel of specialists in business organizations and managers, who provided structured feedback. Based on their recommendations, several items were revised or adapted to better align with the theoretical and practical dimensions of the construct under investigation.
Criterion validity could not be assessed through direct comparison with an existing, equivalent instrument, as no closely aligned scale was administered concurrently. Currently, there is no workplace attachment scale (WAtS) that has been validated specifically for the Spanish population. Although interest in measuring emotional bonds within organizational settings has grown, available instruments have been developed and tested in other cultural contexts. One such example is the WAtS, originally designed and validated in Brazil by De Andrade and Pedruzzi (Reference De Andrade and Pedruzzi2020). This scale assesses secure, anxious, and avoidant attachment styles toward the workplace and has demonstrated strong psychometric properties in a sample of Brazilian workers. However, its applicability to the Spanish population remains untested, highlighting the need for cross-cultural validation or the development of contextually appropriate instruments. Model fit indices offer indirect support for criterion validity. For reference, De Andrade and Pedruzzi (Reference De Andrade and Pedruzzi2020) reported the following standardized fit indices for their motivation scale: AGFI = 0.94, CFI = 0.98, χ2/df = 1.54, and RMSEA = 0.04.
Construct validity was addressed through both exploratory and CFA, as outlined in previous sections. The instrument was intentionally designed with new formulations of items, adapted in wording and orientation to meet the specific aims of this study. As a result, direct comparisons with other existing tools were not deemed appropriate at this stage. However, future research is expected to involve cross-validation against other established instruments, once the current scale’s psychometric structure has been consolidated.
Discussion
A substantial body of research has established the central role of attachment to the workplace (De Andrade & Pedruzzi, Reference De Andrade and Pedruzzi2020). In the Spanish context, so far, no instrument has been formally validated to assess attachment within the workplace setting.
Building on this foundation, the present study proposed a 38-item scale derived from Bowlby’s attachment theory for attachment to organizational contexts. The aim was to evaluate the psychometric properties of the proposed scale in a workforce and managers population drawn from varied activity sectors, with a dual objective: on the one hand, the aim is to develop a scale capable of measuring attachment in the workplace, given the advantages this construct offers in organizational settings. On the other hand, the goal is to identify relational patterns between individuals’ adult attachment styles and the type of attachment developed within the organization, which will serve as the basis for a future line of research.
The results demonstrate strong internal consistency, with a Cronbach’s alpha greater than 0.95. Moreover, the model exhibited similar fit indices compared to those originally reported by Andrade and Pedruzzi (De Andrade & Pedruzzi, Reference De Andrade and Pedruzzi2020) and Scrima et al. (Reference Scrima, Di Carlo, Lorito and Palazzeschi2015; Scrima, Reference Scrima2020), according to current standards of model evaluation (see Section 4.4.). Factor analysis procedures, both exploratory (EFA) and confirmatory (CFA), yielded a final structure of one factor for each dimension.
In the EFA, items with factor loadings above 0.40 were retained, and factor retention was determined via parallel analysis (Horn, Reference Horn1965). The Kaiser–Meyer–Olkin index and Bartlett’s test of sphericity supported the adequacy of the data set for factor analysis. In the CFA, all parameters associated with EFA-derived items were statistically significant (p < .001), providing evidence of convergent and discriminant validity. Most latent factors demonstrated positive intercorrelations between insecure attachment and both negative and secure attachment, as expected. The model proposed here thus offers a valuable framework for future research and practical interventions aimed at fostering workforce and managers’ success. Studying attachment to the workplace is essential because attachment styles, originally developed in early relationships, deeply influence how individuals interact with colleagues, handle stress, and respond to feedback. Securely attached employees tend to build stronger relationships, show greater trust, and adapt better to organizational changes (Harms, Reference Harms2011). In contrast, insecure attachment can lead to conflict, reduced collaboration, and lower job satisfaction (Richards & Schat, Reference Richards and Schat2011).
A validated measure like the WAtS (Scrima et al., Reference Scrima, Di Carlo, Lorito and Palazzeschi2015), for Italian and for the Slovakian population (Greškovičová & Lisá, Reference Greškovičová and Lisá2023), allows organizations to identify these patterns and tailor interventions that foster healthier team dynamics. This understanding can improve leadership development, team cohesion, and overall workplace well-being. However, the main motivation for proposing a new scale, rather than validating the one developed by Scrima et al. (Reference Scrima, Di Carlo, Lorito and Palazzeschi2015) for the Spanish population, is the moderate reliability it has shown in the two populations where it has been tested (Italian Cronbach’s alpha = 0.83 and Slovakian Cronbach’s alpha = 0.65). Moreover, the scale proposed by Scrima et al. did not include any reported analysis of model fit indices. Lisá and Mrázková (Reference Lisá, Mrázková, Pracana and Wang20212021) scale for the Slovakian population showed acceptable fit indices (Table 32).
Table 32. Instruments for measuring attachment in organizational contexts
Source: Authors’ own work.
Beyond the statistical confirmation of the instrument’s psychometric robustness, the implications of these findings suggest important avenues for practical implementation. Managers, Human Resources professionals, and organizational consultants can use the scale as a diagnostic tool to uncover latent relational patterns that may otherwise go unnoticed. By identifying employees with anxious or avoidant tendencies, organizations can implement targeted interventions – such as coaching, mentoring, or group facilitation – to support healthier interpersonal functioning. This is especially relevant in team-based or matrixed structures where collaboration, trust, and psychological safety are essential for high performance.
Another critical insight lies in the potential to use attachment profiling for leadership development. Leadership is increasingly understood as a relational process rather than a positional authority. Leaders with secure attachment styles are more likely to provide consistent emotional availability, respond to employee needs with empathy, and foster high-quality leader–member exchanges. Conversely, leaders with insecure styles may inadvertently contribute to climates of emotional uncertainty or detachment. Thus, integrating attachment awareness into leadership training could yield benefits not only for individual development but also for broader organizational climate and effectiveness.
Finally, the implications of this scale extend into the realm of organizational equity and inclusion. Attachment patterns are not distributed evenly across populations. Individuals from marginalized groups may develop distinct attachment strategies based on early experiences of exclusion or inconsistent support. By identifying these patterns in the workplace, organizations can implement more equitable support structures and design culturally sensitive interventions. Moreover, considering attachment in organizational diagnostics may help address deeper sources of disengagement, turnover, and conflict – issues that are often treated superficially without addressing the underlying emotional and relational roots.
Implications
Theoretical implications
This validated Attachment Scale in the workplace context provides a robust framework to explore how individuals emotionally and cognitively regulate themselves in response to work-related challenges, as well as how they form interpersonal relationships, whether with peers or superiors. Based on Bowlby’s foundational attachment theory (Bowlby, Reference Bowlby1969), the scale helps extend developmental psychology into adult organizational contexts, offering new insights into emotional processes in the workplace (De Andrade & Pedruzzi, Reference De Andrade and Pedruzzi2020). Attachment styles, secure, anxious-ambivalent, and avoidant, interact meaningfully with organizational constructs. By integrating attachment theory with frameworks such as the affective events theory (Weiss & Cropanzano, Reference Weiss and Cropanzano1996) and the job demands-resources model (Bakker & Demerouti, Reference Bakker and Demerouti2013), researchers can better explain how relational schemas shape responses to emotional and cognitive job demands (Katz, Smith & Lopez, Reference Katz, Smith and Lopez2024). This study found that attachment styles significantly predict job performance, burnout, and organizational commitment. These effects were held even after accounting for the Big Five personality traits, highlighting the unique explanatory power of workplace attachment. However, predictive validity is an essential next step, ideally through longitudinal designs linking attachment styles to objective organizational outcomes.
Managerial implications
The Attachment scale has been psychometrically validated and identifies key relational styles, secure, anxious, and avoidant, across workplace contexts. Human resources professionals and managers can use it to assess how individuals relate to coworkers, leaders, and the organization (De Andrade & Pedruzzi, Reference De Andrade and Pedruzzi2020; Greškovičová, Reference Greškovičová2023). Attachment styles are strongly linked to employee well-being. For instance, Vîrgă et al. (Reference Vîrgă, Iliescu and Sava2019a) found that anxious attachment predicts emotional exhaustion, which in turn negatively impacts job performance and satisfaction. Identifying these patterns enables targeted retention strategies and helps prevent burnout. Knowing an employee’s attachment orientation allows for more effective coaching, mentorship, and leadership development programs. Research shows that fostering secure attachment can enhance trust, collaboration, and adaptability, especially in times of organizational change (Greškovičová, Reference Greškovičová2023; Rioux, Reference Rioux2006).
Societal implications
Secure attachment in the workplace is associated with greater openness, trust, and cooperative dynamics. Organizations that recognize and support relational well-being tend to foster psychologically safe cultures that benefit both individuals and teams (Tziner & Sharoni, Reference Tziner and Sharoni2015). Attachment styles are predictive of burnout risk. Anxiously attached employees are more prone to emotional exhaustion and cynicism, which can affect not only individual well-being but also collective morale and organizational sustainability (Vîrgă et al., Reference Vîrgă, Schaufeli, Taris, van Beek and Sulea2019b). Workplace attachment tools can reveal whether underrepresented groups (e.g., women, ethnic minorities, temporary staff) experience higher levels of anxious or avoidant attachment. This insight enables more equitable organizational practices, such as inclusive mentorship programs and bias prevention strategies (Greškovičová, Reference Greškovičová2023; Katz et al., Reference Katz, Smith and Lopez2024).
Conclusions and limitations
This study presents the development and psychometric validation of a culturally adapted instrument designed to measure adult attachment styles within Spanish organizational contexts. Drawing from Bowlby’s attachment theory and incorporating insights from workplace psychology, the scale demonstrates strong internal consistency and construct validity. It effectively distinguishes between secure, avoidant, and anxious-ambivalent attachment styles, offering a valuable tool for both researchers and practitioners seeking to explore relational dynamics in the workplace.
Beyond its methodological contributions, the scale supports a shift in how organizations understand employee behavior – not merely as the result of skills or motivation, but as deeply shaped by emotional and relational patterns. Managers, HR professionals, and organizational consultants can use this instrument to identify attachment-related tendencies that influence trust, communication, teamwork, and resilience. The insights generated by this tool can inform leadership development programs, team interventions, and organizational policies aimed at fostering psychological safety and emotional well-being at work.
Despite its contributions, this study has several limitations. First, data were collected through non-probabilistic LinkedIn-based sampling, which may have introduced self-selection bias and limited generalizability across industries, professional levels, and educational backgrounds. Second, the exclusive reliance on self-reported data raises the possibility of social desirability and introspection biases, while the absence of behavioral measures and longitudinal designs restricts ecological validity and prevents causal inferences about the stability and impact of attachment styles over time. Third, although the sample size was adequate for exploratory and CFA, as other studies have shown, it was not sufficient to conduct subgroup invariance testing or more complex structural modeling; the gender imbalance (65% male) further constrains representativeness. Fourth, while the scale demonstrated strong psychometric properties, concurrent validation with established workplace attachment tools and cross-validation in other cultural contexts were not undertaken, which limits external validity. Fifth, although designed to reflect workplace dynamics, the instrument may not capture all nuanced forms of organizational attachment, particularly in emerging contexts such as hybrid or remote work arrangements, diverse cultural environments, and different hierarchical structures. Finally, although reverse-coded items were included to reduce response bias, their presence may have increased cognitive load or confusion for some respondents. Importantly, item-level analyses (see Tables 7 and 31) indicated that internal consistency remained high (Cronbach’s α > 0.90; McDonald`s ω > 0.95) even when these items were removed, suggesting that their inclusion did not materially affect the psychometric robustness of the scale. Nevertheless, we recognize this as a potential limitation, and future refinements will test simplified or positively worded alternatives to preserve reliability while minimizing respondent burden.
Building on these limitations, several potential lines of inquiry for future research can be outlined. First, replication with larger and more demographically balanced samples is essential to allow subgroup analyses, invariance testing, and broader generalizability across industries, professional levels, and educational backgrounds. Second, longitudinal designs are needed to assess the stability of workplace attachment styles over time and to establish their predictive validity for key organizational outcomes such as job performance, burnout, turnover, and career development. Third, incorporating multi-method assessments, including peer and supervisor ratings, behavioral observations, and triangulation with objective indicators, would reduce reliance on self-reports and strengthen validity. Fourth, concurrent administration of established workplace attachment scales will provide stronger evidence of criterion validity, while cross-cultural studies in other Spanish-speaking and international contexts will clarify the instrument’s broader applicability. Fifth, refinement of reverse-coded items and expansion of the item pool could help minimize respondent confusion and ensure coverage of emerging workplace realities such as remote or hybrid work arrangements, cultural diversity, and hierarchical variations. And, finally, the integration of both categorical and dimensional approaches to attachment may further enrich theoretical understanding while maintaining the practical utility of the scale in organizational contexts.
Summarizing, this study marks a step forward in bridging psychological theory and organizational practice. By providing a reliable and context-specific instrument to assess adult attachment styles in professional and workforce settings, it opens the door to more emotionally intelligent, inclusive, and human-centered organizational cultures. Such a tool is not only timely but essential in a world where relational capacity and emotional resilience are increasingly critical to individual and organizational success.
Data Availability Statement
The data collected will not be transferred without the express consent of the participants, except in cases where there is a legal obligation to do so. Personal data will be kept only for the duration of the project. Raw data that support the findings of this study are available upon reasonable request from the corresponding author, J.J.R.-G. The data are not publicly available due to restrictions from the Research Ethics Committee because they contain information that compromises the privacy of the participants in the research.
Author Contributions
J.J.R.G.: Theoretical framework, methodology, analysis and results, model validation, and discussion. E.I.V.M.: Theoretical framework, methodology, data curation and evaluation, discussion, and conclusions. D.L.S.M.: Introduction, theoretical framework, instrument design, and grading. D.R.V.: Theoretical framework, methodology, analysis and results, discussion and conclusions. All authors read and approved the final manuscript.
Competing Interests
Authors have no competing interests as defined by JMO, or other interests that might be perceived to influence the interpretation of the article.
Ethical Standards
The research work obtained the favorable consent of the Research Ethics Committee of the Rey Juan Carlos University. All participants were informed of the objective of the study, its scope and marked their consent on the form itself about their intention to participate. The data controller, the consent and purpose of the study, the communication of the data, the conservation of the data and the exercise of their rights of access, rectification, deletion, limitation of processing, opposition and others recognized by the General Data Protection Regulation, as well as by Organic Law 2/2018, were informed of Personal Data Protection and guarantee of Digital Rights. The personal data collected will not be transferred without the express consent of the participants, except in cases where there is a legal obligation to do so. Personal data will be kept only for the duration of the project.
Consent for Publication
The authors authorize the publisher to proceed with the publication of the research work if the publisher deems it necessary and passes the manuscript review phases.
Authors’ information
Authors presented this research at the BENI Conference 2025 Business, Entrepreneurship & Innovation held online, June 30 and July 1, 2025.
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