Well-being has become a pressing concern in the modern workplace, with stress, burnout, and other issues on the rise. Evidence suggests that well-being issues can result in reduced productivity, increased absenteeism, and medical expenses for organizations [1,2], as well as impact teamwork, decision-making, and innovation [3]. By addressing well-being in the workplace, organizations can create a healthier culture and work environment, which can result in increased employee engagement, performance, and productivity, as well as better financial outcomes and retention [4]. Moreover, fostering workplace well-being can have broader societal benefits, such as reducing health care burdens, promoting mental health awareness, and contributing to overall community well-being [5-7]. Therefore, it is crucial to prioritize well-being in the workplace, and digital health tools offer promising solutions for achieving this goal.

In recent years, there have been calls for digital health implementation in workplace settings [8]. Although the digital health market is thriving, with over 350,000 products available and a growth rate of 25% per year [9], digital health technologies for the workplace are minimal, and existing ones focus on employees at the individual level and do not address team and organizational workplace issues [10]. Recognizing the need for digital health interventions, the World Health Organization [11] and the European Commission [12] have published guidelines for digital health tools, with the main objective of evidence-based practice. A key problem with existing digital health products is that the regulation around them is minimal [13]. The majority of these products do not always reach the basic standards of scientific rigor, such as peer-reviewed publications, with only 2.08% being evidence-based [14]. Since traditional approaches, such as employee assistance programs, are challenging to reach and have low uptake [15] and remote and hybrid work is rising, there is a need for evidence-based digital health solutions in the workplace.

According to Stevenson and Farmer [8], well-being measurement is a crucial workplace core standard for employees and teams to monitor well-being and take positive action to improve it. It also enables team leads and organizations to use the results to establish appropriate well-being strategies and enhance organizational well-being in general. Therefore, there is a crucial need for a robust well-being measurement instrument in the workplace for employees, teams, and organizations. One platform that aims to fulfill the need for such solutions is Quan, a digital well-being platform for employees, teams, and organizations, which has a 3-fold process: (1) quantify well-being at employee, team, and organizational levels; (2) provide comprehensive and personalized well-being insights as well as information on the underlying reasons; and (3) deliver tailored interventions for individual employees and teams. Our research is the first step toward this approach and concerns the development of a novel, valid, and reliable measurement instrument that assesses well-being at the workplace and in personal life. This instrument is called the Quan Well-being Index (QWI).

The development of a novel, valid, and reliable measurement instrument for the well-being of employees, teams, and organizations, which will be used in a digital setting, is of pivotal importance. Currently, no measurement instrument assesses well-being in both personal and work life. A plethora of measures exist for assessing various well-being aspects of personal life. Despite the growth of self-report well-being questionnaires, there is significant variation in their conceptualization of well-being (eg, eudemonic and hedonic well-being, and quality of life) and their methodological aspects such as length and psychometric properties [16]. Furthermore, the majority of available measures address well-being in general or in personal life (eg, the Warwick-Edinburgh Mental Well-being Scale [17]) or focus on only 1 aspect, such as quality of life (eg, Quality of Life Inventory [18]). Moreover, the majority of well-being measures prioritize mental well-being over aspects related to physical health, such as sleep, nutrition, and exercise. On the other hand, the assessment of well-being in domain-specific settings, such as work, is still in its infancy, with only a few existing validated measures [19-21] that capture only workplace-related well-being such as job satisfaction, burnout, and stress [22-24]. To establish a comprehensive model of occupational well-being, work-related and personal facets need to be considered [25].

Various theoretical models have been developed to explain the factors that contribute to well-being in the workplace, with particular emphasis on the interaction between job characteristics and psychological needs. Among these, the Job Demands-Resources (JD-R) model and Self-Determination Theory (SDT) have emerged as 2 of the most influential frameworks, offering complementary perspectives on how workplace conditions and intrinsic motivation shape well-being. The JD-R model [26] stands out as the primary framework for conceptualizing the drivers of employee well-being, and its effectiveness is, in part, attributed to its suitability in interpreting interventions within the workplace [27-29]. According to the JD-R model, the mental well-being of workers results from the interplay of 2 distinct categories: job demands and job resources. Job demands encompass the various facets of work, such as physical, psychological, social, or organizational, that necessitate sustained effort, whether it be physical, cognitive, or emotional [27]. Job resources refer to the physical, psychological, social, or organizational elements of work that have the potential to motivate, assist in achieving work-related goals, mitigate the effects of job demands, and foster personal development and learning [27]. Beyond workplace factors, the JD-R model also acknowledges the role of personal demands and resources in shaping well-being. Personal demands refer to individual characteristics or life circumstances, such as caregiving responsibilities, financial stress, and chronic health conditions, that require effort and may contribute to strain [30]. Conversely, personal resources, including resilience, self-efficacy, optimism, and emotional intelligence, can help employees cope with challenges, enhance motivation, and buffer the negative effects of high job demands [30]. The interaction between job-related factors and personal factors is crucial, as personal resources can amplify the benefits of job resources, while personal demands may exacerbate workplace stressors, further influencing overall well-being.

The SDT has emerged as a crucial framework for understanding and promoting well-being in the workplace. Grounded in the work of Ryan and Deci [31], the SDT highlights the fundamental psychological needs of autonomy, competence, and relatedness, asserting that meeting these needs is essential for ideal human functioning and well-being [31]. In the workplace, the SDT has been instrumental in explaining the impact of autonomy on employee motivation and satisfaction [32]. When individuals perceive a high degree of autonomy in their work, they could have increased job satisfaction and engagement [33]. Furthermore, the fulfillment of competence needs, achieved through opportunities for skill development and feedback, is linked to enhanced job performance and personal well-being [34]. Finally, creating a workplace environment that supports relatedness and fosters positive social connections and interpersonal relationships has been linked with increased levels of well-being and job satisfaction [35]. Thus, the application of the SDT in the workplace not only contributes to individual well-being but also holds promise for enhancing organizational outcomes. However, so far, no measurement instrument of workplace and personal life well-being has considered the JD-R model and the SDT. Therefore, there is a need for a novel, holistic, and robust measurement instrument that takes into consideration these frameworks and simultaneously assesses well-being at the workplace and in personal life, as these settings are intricately associated.

The development of a digital workplace and personal life well-being index will support employees at the individual level to track, reflect, act on, and ultimately improve their well-being. Existing evidence suggests that digital mental health platforms that provide measurement scores to their users may improve their mental health by supporting them to be aware of and reflect on it [36,37]. At the team level, the index will act as a catalyst for establishing bidirectional well-being communication between employees and their team leads, which has been shown to contribute to improved well-being and increased trust between them [38]. Furthermore, such a measurement instrument will support users in assessing and monitoring their well-being across time by identifying areas of strength and risk and subsequently the impact of tailored interventions. Finally, at the organizational level, the index will provide organizations with metrics that will help them identify which well-being initiatives they should invest in and offer to their employees. This, in turn, will lead to improved employee and team well-being and better functioning organizations.

The primary objective of this project is to create and validate a comprehensive self-report tool called the QWI. This instrument aims to evaluate the complete range of well-being aspects in both professional and personal domains for individuals, teams, and organizations. Building upon existing well-being theories and models, this research encompasses 3 studies focused on developing and refining the QWI using a British sample. Study 1 details the creation of the initial item pool and the process to ensure face and content validity. Study 2 describes the development of the QWI, using data collected from online panels to explore the factor structure. Study 3 employs a separate sample to verify the structure of the QWI and examines various models using a confirmatory approach. Additionally, study 3 reports on the internal reliability, convergent and divergent validity, and test-retest reliability of the QWI through psychometric indicators.

The aim is to develop and validate a novel, psychometrically robust self-report instrument called the QWI, which is designed to assess well-being across both the workplace and personal life domains. The QWI seeks to capture individual, team, and organizational well-being to support digital health applications in workplace settings.

We report on the development of the QWI, a novel self-report index that measures well-being in personal life and at the workplace. The factors identified in this index encompass, corroborate, and quantify aspects of well-being that have previously only been examined in isolation, integrating them into a single measurement instrument for the first time [39,55]. The development of QWI factors has also generated new insights into well-being in personal life and at the workplace, which are presented below.

The development and validation of the QWI as a novel and holistic measure of well-being in personal life and at the workplace have been demonstrated through a series of studies, showing good internal validity, convergent and divergent validity, and test-retest reliability. This comprehensive tool encompasses 5 key factors that collectively provide a holistic well-being assessment.

The first factor “thrive and connect in personal life” covers various aspects of personal life, including emotional state, mindfulness, relationships, social support, engagement, and sense of purpose. These results indicate that well-being in personal life is a multifaceted concept, encompassing various interconnected elements that contribute to an individual’s overall life satisfaction and psychological health [39,66]. The second factor “thrive and connect at work” covers various aspects of work life, such as emotions, relationships, personal growth, and feeling valued, aligning with prior research emphasizing the importance of workplace well-being [26,31]. The third factor “mental health” emphasizes the need to consider mental health issues in both personal and professional contexts, recognizing that individuals may experience different levels of feelings (eg, stress) in personal life and at the workplace [66]. The fourth factor “physical health” is an essential aspect of holistic well-being that covers characteristics related to physical activity and nutrition, consistent with research highlighting the interdependence of physical and psychological health [40,67].

The presence of a general well-being factor above the 4 group factors (thrive and connect in personal life, thrive and connect at work, physical health, and mental health) suggests that well-being is best conceptualized as a higher-order, integrative construct that unites experiences across both personal and professional life domains. This supports the growing body of research emphasizing the systemic and interrelated nature of well-being across life domains [68,69].

Theoretically, this structure resonates with recent multidimensional and ecological models of well-being [70,71], which move beyond binary hedonic or eudaimonic frameworks and instead frame well-being as a dynamic model influenced by physical, psychological, social, and contextual factors. The QWI’s higher-order structure reflects this complexity, recognizing that individual well-being outcomes do not occur in isolation but are shaped by conditions both at the workplace and in personal life.

Furthermore, the finding that thrive and connect in personal life and thrive and connect at work load onto a common higher-order factor challenges the often rigid boundaries between occupational and personal well-being that dominate traditional models. This aligns with the “whole person” perspective emerging in organizational psychology [72,73], which posits that work and nonwork experiences are mutually influential. For instance, positive interpersonal dynamics at work can buffer stress in personal life, while strong personal relationships may enhance workplace engagement and mood [67].

QWI’s hierarchical structure is broadly consistent with prominent multidimensional models of well-being, including the PERMA model [39], which conceptualizes well-being as a composite of positive emotion, engagement, relationships, meaning, and accomplishment. However, the QWI makes a distinctive contribution by operationalizing both domain-specific well-being (thrive and connect at work vs thrive and connect in personal life) and foundational health factors (physical health and mental health) within a single integrated measurement framework. This dual focus on “where” well-being is experienced and “how” it is sustained may extend existing models by offering a more pragmatic approach for organizational interventions.

The presence of the “thrive and connect” concept as a factor both in personal life and at the workplace indicates that there is a need for distinction between aspects that take place in different settings. As such, individuals are provided with a tool to track and take action on their well-being in separate contexts, which might require different approaches. For example, issues related to work could be brought up in one-to-one meetings between employees and their managers to facilitate bidirectional communication about aspects that might not be apparent in one’s work but can be adjusted to promote healthier organizations [74]. Moreover, the ability to differentiate between personal and professional well-being factors could lead to more targeted interventions and support systems both at the individual level and within organizational structures, ultimately contributing to a more holistic approach to well-being management.

From a practical standpoint, the presence of a general well-being factor allows for both macro- and micro-level analysis. At the macro level, the general factor serves as a useful indicator of an individual’s or team’s holistic well-being, enabling organizations to track broad shifts over time or following interventions. At the micro level, the 4 factors facilitate precise diagnostics, allowing leaders or practitioners to identify specific areas (eg, workplace social connectedness vs mental health) that require tailored support.

Scoring is structured to align with the hierarchical factor model validated in study 3. Each item contributes to 1 of 4 factors: thrive and connect in personal life, thrive and connect at work, physical health, and mental health. Factor scores are calculated by averaging responses to the items that belong to each factor, and the overall QWI score is the average of the 4 factors. For interpretative purposes in applied settings, we offer the following score ranges: scores of 0.0-1.9 suggest low well-being and may indicate risk, scores of 2.0-3.9 reflect moderate well-being, and scores of 4.0-6.0 indicate high well-being or “thriving.” These guidelines are intended to facilitate meaningful interpretation and intervention planning by researchers, practitioners, and organizational stakeholders.

A key contribution of the QWI lies in its integrated assessment of both the personal and professional domains of well-being within a single, psychometrically validated instrument. While several established measures of well-being exist, such as the Warwick-Edinburgh Mental Well-being Scale [17], World Health Organization-5 Well-being Index [54], and PERMA Profiler [75], these tend to focus on general mental well-being and positive functioning, often without capturing the complex interplay between work and nonwork settings.

The QWI addresses this gap by explicitly incorporating 4 interrelated dimensions: thrive and connect in personal life, thrive and connect at work, physical health, and mental health. This structure allows for the simultaneous assessment of cross-domain experiences and provides a more ecologically valid representation of how individuals experience well-being across the life course. In contrast, measures like the Job Satisfaction Survey [76] or the Utrecht Work Engagement Scale [77] focus narrowly on occupational well-being, whereas personal well-being tools, such as the Ryff Psychological Well-being Scales [78], do not account for work-related dynamics.

From a practical standpoint, the QWI is designed for ease of use in organizational settings. It comprises 35 items, takes approximately 5 to 7 minutes to complete, and uses a uniform 7-point Likert response scale ranging from “Never” (0 points) to “Always” (6 points). This balance between comprehensiveness and brevity makes it well suited for routine monitoring in time-constrained environments, a feature less common in longer instruments like Ryff scales (84 items) or multidimensional surveys requiring separate administration for work and nonwork domains.

Moreover, by capturing personal and professional well-being within 1 coherent framework, the QWI reduces the burden on respondents and provides practitioners with an integrated profile that enhances intervention planning. This is particularly advantageous in applied settings where holistic well-being strategies (eg, action planning, leadership feedback, and human resource initiatives) benefit from a unified data source. However, we acknowledge that combining domains may reduce granularity in highly specialized research contexts, which remains a consideration when choosing between integrated and domain-specific tools.

Taken together, the QWI’s content coverage, time-efficient administration, and psychometric strength position it as a novel and practical addition to the well-being assessment landscape, particularly for contexts requiring cross-domain insights and targeted, team-level interventions.

Certain limitations and future directions that stemmed from the outcomes of this research need to be addressed. The United Kingdom–based sample we recruited may limit the generalizability of the findings to other cultures, for example, non-Western cultures [79]. Validation in other countries might require the inclusion or exclusion of certain items to support different conceptualizations of well-being [80]. For example, in countries that have indigenous populations, such as New Zealand and Australia, items that represent family, land, and rituals might be necessary to encompass their well-being experiences [81]. We are planning to translate and validate the QWI for other continents as well as countries across Europe to explore how well it maps in other languages and what further improvements need to be made. In doing so, particular care will be taken to ensure conceptual, linguistic, and metric equivalence across cultural contexts, which may include exploratory and confirmatory factor analyses in each new language group.

Additionally, although the QWI demonstrated good convergent validity with established well-being measures, all data were derived from self-report instruments. This mono-method approach may introduce shared method variance and raise concerns about response biases, including social desirability and acquiescence effects [82]. To strengthen construct validity and provide a more holistic view of well-being, future studies should incorporate a multimethod approach. This may include behavioral data (eg, absenteeism rates or job performance metrics) and objective physiological indicators, such as cortisol levels, heart rate variability, and sleep quality measures, which can serve as indirect proxies for stress and overall health.

Lastly, while the 7-point Likert response format (ranging from “Never” to “Always”) was chosen based on evidence suggesting that it improves reliability and reduces response bias, it may not be optimal in all cultural or linguistic contexts. Adaptations to the scale’s format may be necessary when validating the QWI globally, particularly in regions where numeric or verbal anchors are interpreted differently due to linguistic or cultural norms.

By addressing these limitations, future research will be able to further assess the utility, adaptability, and impact of the QWI as a cross-culturally valid and practically useful tool for measuring employee well-being across personal and professional life domains.

In summary, the QWI is a novel, reliable, and validated instrument that systematically measures multiple and distinct aspects of well-being in personal life and at the workplace. It is anticipated that the QWI will be valuable to digitally assess well-being, enabling individuals, teams, and organizations to gain insights and monitor their progress over time, implement appropriate interventions, and ultimately enhance well-being areas that require improvement.