The symbolizations emerging from aviation crew members’ perspectives on well-being: a linguistic analysis using emotional text mining
Articolo
Data di Pubblicazione:
2025
Citazione:
The symbolizations emerging from aviation crew members’ perspectives on well-being: a linguistic analysis using emotional text mining / Renzi, Alessia; Reho, Matteo; Tomai, Manuela; Scialanga, Micaela; Cordella, Barbara. - In: FRONTIERS IN PSYCHOLOGY. - ISSN 1664-1078. - 16:(2025), pp. 01-08. [10.3389/fpsyg.2025.1612940]
Abstract:
Background: Well-being is a complex and structured construct recently studied in aviation, primarily through self-report measures. The primary aim of this study is to explore aviation crews’ representations of well-being using the Emotional Text Mining (ETM) method. A secondary aim is to examine whether different representations are associated with occupational variables.
Method: 492 participants (302 males) completed an online survey via SurveyMonkey, including an open-ended question prompting them to describe their perception of well-being. Additionally, socio-occupational variables were collected. The texts were analyzed using ETM, identifying how a social group emotionally symbolizes a topic.
Results: The analysis revealed three clusters: (1) Material and Family Stability, (2) Individual Self-Development, and (3) Connection and Social Realization. These clusters are positioned within a factorial space defined by two factors: one contrasting individual vs. social representations of well-being and the other differentiating well-being as a set of given elements vs. an active, evolving process. No associations with occupational variables were found.
Conclusion: The findings suggest a concept of well-being in which the work dimension is considered only marginally, primarily for its material and economic value, and not as part of a broader sense of personal fulfillment. Administering the survey within a workplace setting may have heightened social desirability bias, potentially influenced by fears of professional repercussions.
Tipologia CRIS:
Articolo su rivista
Keywords:
well-being; aviation; aviation crew members; emotional text mining; psychological
service
Elenco autori:
Renzi, Alessia; Reho, Matteo; Tomai, Manuela; Scialanga, Micaela; Cordella, Barbara
Link alla scheda completa:
Link al Full Text:
Pubblicato in: