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.

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. - (2025), pp. 01-08. [10.3389/fpsyg.2025.1612940]

The symbolizations emerging from aviation crew members’ perspectives on well-being: a linguistic analysis using emotional text mining

Matteo Reho;
2025

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.
2025
18-giu-2025
01
08
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. - (2025), pp. 01-08. [10.3389/fpsyg.2025.1612940]
Renzi, Alessia; Reho, Matteo; Tomai, Manuela; Scialanga, Micaela; Cordella, Barbara
File in questo prodotto:
File Dimensione Formato  
fpsyg-1-1612940.pdf

Open access

Tipologia: VOR - Versione pubblicata dall'editore
Licenza: [IR] creative-commons
Dimensione 416.8 kB
Formato Adobe PDF
416.8 kB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

Licenza Creative Commons
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1387648
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact