Psychologists Build a Grit Scale for Factory Workers on Thailand’s Automotive Assembly Lines

Grit, the much-celebrated blend of perseverance and passion for long-term goals, has become one of the most talked-about concepts in modern psychology. Yet a new study from Thailand suggests that the standard questionnaires used to measure it may miss something essential about how determination actually looks on a factory floor. In research published in Discover Psychology, a team at the Behavioral Science Research Institute of Srinakharinwirot University set out to build a grit scale tailored specifically to the people who keep the automotive industry moving: the operators who stand at production lines day after day, often for decades. The result is a carefully constructed 15-item instrument that captures the rhythm of sustained effort in tightly coupled manufacturing work, while also revealing how difficult it is to separate perseverance from passion once they are embedded in a single workplace culture.

The study, led by Suricha Artamaprasangsa with colleagues Sudarat Tuntivivat and Polthep Poonpol, began from a deceptively simple observation. Existing grit measures, most famously the scale developed by psychologist Angela Duckworth, were designed largely around individual, self-directed pursuits such as education, military training, or competitive pursuits. Manufacturing work is different in kind. On an automotive assembly line, effort is synchronized with machines and colleagues, goals are collective rather than personal, and long-term commitment is expressed through attendance, precision, and adherence to disciplined routines rather than through individual ambition. The researchers argued that a generic questionnaire might fail to detect the distinctive behavioral signatures of grit in this environment, and that a context-specific instrument was needed before anyone could meaningfully measure, predict, or cultivate persistence among production workers.

To build that instrument, the team adopted a sequential exploratory mixed methods design, an approach that deliberately puts qualitative discovery first and statistical confirmation second. In the qualitative phase, eight supervisors and senior supervisors with between 20 and 35 years of production experience took part in semi-structured interviews. These were not casual conversations; they were structured probes into what sustained effort and long-term commitment actually look like in observable behavior on the line. The researchers then applied a hybrid deductive-inductive thematic analysis, a technique that both tests existing theoretical categories and allows new themes to emerge from the data itself. Crucially, the analysis retained the two established dimensions of grit, perseverance of effort and consistency of interest, while also surfacing ten contextual behavioral indicators that generic scales had never captured.

Those ten indicators form the conceptual heart of the new scale. Drawing on the interview material, the researchers wrote two questionnaire items for each indicator, producing an initial pool of 20 items. Before any large-scale testing, the pool was subjected to two rounds of scrutiny. First, five independent experts assessed each item for congruence with its intended construct and for clarity of wording, a standard procedure in scale development designed to weed out ambiguous or double-barreled questions. Second, 30 automotive operators completed a pilot version of the scale, providing early evidence about how the items functioned with the very population they were written for. Only after this filtering did the team move into the quantitative phase, in which 204 operational employees completed the full instrument.

The statistical analysis that followed was rigorous and transparent. Five items were removed based on combined evidence from the pilot test and a confirmatory factor analysis, the technique psychologists use to test whether a proposed structure of a questionnaire actually matches the pattern of responses people give. The researchers then estimated the remaining model using diagonally weighted least squares, an estimation method well suited to the ordered categorical response formats typical of Likert-scale questionnaires. The final model contained 15 items organized into two correlated factors, and its fit statistics were strikingly good: a chi-square of 165.45 with 89 degrees of freedom, a comparative fit index of 0.999, a Tucker-Lewis index of 0.999, a root mean square error of approximation of 0.065 with a 90 percent confidence interval of 0.049 to 0.080, and a standardized root mean square residual of just 0.038. In plain terms, the two-factor structure described the data almost perfectly.

But the story took an intriguing turn when the researchers compared this two-factor solution against a simpler one-factor alternative. The correlated two-factor model showed better descriptive fit than the single-factor model, suggesting that perseverance and passion are not identical. Both dimensions also demonstrated high internal consistency, meaning the items within each factor hung together reliably. Yet when the team examined the relationship between the two factors themselves, they found a latent correlation of 0.938 and a heterotrait-monotrait ratio, or HTMT, of 0.937. Both figures hover near the ceiling of what psychometricians consider acceptable for treating two constructs as genuinely distinct. In practical terms, the perseverance and passion factors were so tightly intertwined that the study could not establish discriminant validity, the demonstration that two supposedly separate traits are actually measuring different things.

The authors are refreshingly candid about this limitation. Their findings, they write, provide only preliminary support for a highly correlated two-factor measure, and they caution against interpreting the subscales separately or using them for high-stakes decisions such as hiring or promotion. They offer a compelling interpretation of the pattern: what looks like two factors may in fact reflect systemic discipline, a contextual pattern in which sustained effort and long-term commitment fuse into a single way of working within the structured environment of automotive manufacturing. In a factory, showing up consistently, maintaining precision, and committing to the long haul are not independent choices but interlocking habits reinforced by the production system itself. Grit in this setting may be less a matter of two separable psychological muscles and more a single, deeply embedded occupational disposition.

The implications reach well beyond Thailand’s automotive sector. For organizations, the study is a reminder that psychological constructs do not travel unchanged across contexts. A questionnaire validated on university students may quietly mismeasure the same trait in a welder, a nurse, or a logistics worker, and decisions based on such mis measurement can be costly and unfair. For researchers, the work illustrates the value of mixed methods scale development: qualitative interviews with experienced practitioners generated behavioral indicators no literature review alone would have produced, and quantitative modeling then tested whether those indicators formed a coherent, measurable structure. The two phases corrected each other, with the pilot data and confirmatory analysis trimming the initial 20-item pool down to a leaner, better-fitting 15-item instrument.

The study also contributes to a growing international conversation about the cultural boundaries of grit. Critics of grit research have long argued that the construct may reflect culturally specific ideals of individual striving, and that in collectivist settings, persistence is often expressed through loyalty to a team, a company, or a shared production goal. The Thai findings lend weight to that critique while offering a constructive path forward: rather than abandoning grit, researchers can rebuild its measurement from the ground up within each occupational and cultural context, letting the people who live the construct define its observable forms. The ten contextual indicators identified here, distilled from more than two centuries of combined supervisory experience, offer a template for how such reconstruction can proceed.

Much work remains before the new scale can be used with confidence. The authors explicitly call for independent replication, external validity testing against outcomes such as job performance or retention, and measurement invariance testing to confirm that the scale functions equivalently across different groups of workers. The sample of 204 employees, while adequate for confirmatory factor analysis, is drawn from a single industry in a single country, and the near-perfect correlation between factors means the two-factor structure may yet collapse into one. Still, the study stands as a model of methodological honesty: it reports stellar fit statistics and then immediately flags the discriminant validity problem that a less careful team might have buried. In a field often criticized for overclaiming, that combination of ambition and restraint may be the most durable form of grit on display.

Subject of Research: Development and psychometric validation of a context-specific grit scale for Thai automotive production workers

Article Title: A mixed methods development of a grit scale for Thai automotive operators

Article References: A mixed methods development of a grit scale for Thai automotive operators. (n.d.). https://doi.org/10.1007/s44202-026-00934-x

Image Credits: AI Generated

DOI: 10.1007/s44202-026-00934-x

Keywords: grit, scale development, psychometrics, mixed methods, automotive operators, Thailand, confirmatory factor analysis, perseverance, occupational psychology, measurement invariance, manufacturing, survey methodology