The purpose of this study was to investigate how the use of jargon in workplace communication affects employees’ processing fluency, self-efficacy, and their intentions to seek and share information. This study employed an experimental design involving 1,826 participants randomly assigned to either a jargon or no-jargon condition. Participants were asked to imagine starting a new job and received an email containing either jargon-laden or jargon-free language. The results suggest that the use of jargon not only impairs processing fluency but also undermines employees’ confidence in their self-efficacy to complete work tasks, which ultimately reduces effective communication through information seeking and sharing intentions. This underscores the need for organizations to be mindful of language complexity to promote better information flow and team dynamics.
AlterA. L.OppenheimerD. M. (2009). Uniting the tribes of fluency to form a metacognitive nation. Personality and Social Psychology Review, 13(3), 219–235.
2.
AjzenI. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211.
3.
AvnetT.PhamM. T.StephenA. T. (2012). Consumers’ trust in feelings as information. Journal of Consumer Research, 39(4), 720–735. https://doi.org/10.1086/664978
4.
BullockO. M.Colón AmillD.ShulmanH. C.DixonG. N. (2019). Jargon as a barrier to effective science communication: Evidence from metacognition. Public Understanding of Science, 28(7), 845–853. https://doi.org/10.1177/0963662519865687
5.
BullockO. M.ShulmanH. C. (2021). Utilizing framing theory to design more effective health messages about tanning behavior among college women. Communication Studies, 72(3), 319–332.
6.
ClarkH. H.BrennanS. E. (1991). Grounding in communication. In ResnickL. B.LevineJ. M.TeasleyS. D. (Eds.), Perspectives on socially shared cognition (pp. 127–149). American Psychological Association.
7.
CherianJ.JacobJ. (2013). Impact of self efficacy on motivation and performance of employees. International Journal of Biometrics, 8, Article 80. https://doi.org/10.5539/IJBM.V8N14P80.
DrewP.HeritageJ. (1992). Talk at work: Interaction in institutional settings. Cambridge University Press.
10.
ErgünE.AvcıÜ. (2017). Knowledge sharing self-efficacy, motivation, and sense of community as predictors of knowledge receiving and giving behaviors. Knowledge Management & E-Learning, 9(1), 39–51. https://doi.org/10.34105/j.kmel.2017.09.003
FiskeS. T.TaylorS. E. (1991). Social cognition (2nd ed.). McGraw-Hill.
13.
GersickC. J. G.HackmanJ. R. (1990). Habitual routines in task-performing groups. Organizational Behavior and Human Decision Processes, 47(1), 65–97. https://doi.org/10.1016/0749-5978(90)90047-D
14.
GumperzJ. J. (1982). Discourse strategies. Cambridge University Press.
15.
HayesA. F. (2018). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach (2nd ed.). Guilford Press.
16.
HsiehJ. J. P. A.KeilM.WangX.TiwanaA.SnehaS. (2021). The role of psychological ownership and knowledge sharing in open source software project success. Information & Management, 58(3), Article 103442. https://doi.org/10.1016/j.im.2020.103442
17.
IpeM. (2003). Knowledge sharing in organizations: A conceptual framework. Human Resource Development Review, 2, 337–359. https://doi.org/10.1177/1534484303257985.
KahlorL.YangJ.LiX.WangW.OlsonH. C.McNeillL. S. (2020). Environmental information seeking and sharing: The role of planned risk information seeking. Environment and Behavior, 52(8), 870–902. https://doi.org/10.1177/0013916519853286
20.
KuoF. Y.YoungM. L. (2008). A study of the intention–action gap in knowledge sharing practices. Journal of the American Society for Information Science and Technology, 59(8), 1224–1237. https://doi.org/10.1002/asi.20816
21.
ManikaD.WellsV. K.Gregory-SmithD.GentryM. (2017). The impact of individual attitudinal and organizational variables on workplace environmentally friendly behaviors. Journal of Business Ethics, 140(3), 517–534. https://doi.org/10.1007/s10551-015-2670-9
22.
MarlowS. L.LacerenzaC. N.PaolettiJ.BurkeC. S.SalasE. (2018). Does team communication represent a one-size-fits-all approach?: A meta-analysis of team communication and performance. Organizational Behavior and Human Decision Processes, 144, 145–170. https://doi.org/10.1016/j.obhdp.2017.08.001
23.
Mei-HsiangW.Shih-CheL.Tarng-YaoY. (2014). Understanding the antecedents of team performance: The importance of an expertise-centered coordination. Asia Pacific Management Review, 19(2), 151–172. https://doi.org/10.6126/APMR.2014.19.2.03
24.
Mesmer-MagnusJ.DeChurchL. (2009). Information sharing and team performance: A meta-analysis. The Journal of Applied Psychology, 94 2, 535–546. https://doi.org/10.1037/a0013773
25.
MorelandR. L.LevineJ. M. (1982). Socialization in small groups: Temporal changes in individual-group relations. Advances in Experimental Social Psychology, 15, 137–192.
26.
NiemiR. G.CraigS. C.MatteiF. (1991). Measuring internal political efficacy in the 1988 National Election Study. American Political Science Review, 85(4), 1407–1413. https://doi.org/10.2307/1963953
27.
PatokoN.YazdanifardR. (2014). The Impact of Using Many Jargon Words, while Communicating with the Organization Employees. American Journal of Industrial and Business Management, 4, 567–572. https://doi.org/10.4236/AJIBM.2014.410061.
28.
RentschJ. R.DeliseL. A.SalasE.LetskyM. P. (2010). Facilitating knowledge building in teams: Can a new team training strategy help?Small Group Research, 41, 505–523. https://doi.org/10.1177/1046496410369563
29.
RiggsE. E.ShulmanH. C.LopezR. (2022). Using infographics to reduce the negative effects of jargon on intentions to vaccinate against COVID-19. Public Understanding of Science, 31(6), 751–765.
30.
RimalR. N. (2006). Perceived risk and self‑efficacy as motivators: Understanding individuals’ long‑term use of health information. Journal of Communication, 56(1), 45–68.
31.
SalasE.RosenM. A.BurkeC. S.GoodwinG. F. (2009). The wisdom of collectives in organizations: An update of the teamwork competencies. In SalasE.GoodwinG. F.BurkeC. S. (Eds.), Team effectiveness in complex organizations: Cross-disciplinary perspectives and approaches (pp. 39–79). Taylor & Francis.
32.
ScheerhornD.GeistP.TeboulJ. C. B. (1994). Beyond decision making in decision-making groups: Implications for the study of group communication. In FreyL. R. (Ed.), Group communication in context: Studies of natural groups (pp. 247–262). Erlbaum.
33.
SchwarzN. (2010). Feelings-as-information theory. In Van LangeP. A. M.KruglanskiA. W.HigginsE. T. (Eds.), Handbook of theories of social psychology. Sage.
34.
SchwarzN. (2015). Metacognition. In M. Mikulincer, P. R. Shaver, E. Borgida, & J. A. Bargh (Eds.), APA handbook of personality and social psychology: Attitudes and social cognition (pp. 203–229). APA.
35.
SchwarzN.CloreG. L. (1983). Mood, misattribution, and judgments of well-being: Informative and directive functions of affective states. Journal of Personality and Social Psychology, 45(3), Article 513.
36.
SchwarzN.CloreG. L. (2007). Feelings and phenomenal experiences. In KruglanskiA. W.HigginsE. T. (Eds.), Social psychology: Handbook of basic principles (2nd ed., pp. 385–407). Guilford Press.
37.
SextonB. J.HelmreichR. L. (2000). Analyzing cockpit communications: The links between language, performance, error, and workload. Human Performance in Extreme Environments, 5, 63–68.
38.
SharonA. J.Baram-TsabariA. (2014). Measuring mumbo jumbo: A preliminary quantification of the use of jargon in science communication. Public Understanding of Science, 23(5), 528–546. https://doi.org/10.1177/0963662512469916
39.
ShulmanH. C.DixonG. N.BullockO. M.Colón AmillD. (2020). The effects of jargon on processing fluency, self-perceptions, and scientific engagement. Journal of Language and Social Psychology, 39(5–6), 579–597. https://doi.org/10.1177/0261927X20902177
40.
ShulmanH. C.SweitzerM. D. (2018). Advancing framing theory: Designing an equivalency frame to improve political information processing. Human Communication Research, 44(2), 155–175. https://doi.org/10.1093/hcr/hqx006
41.
ShulmanH. C.SweitzerM. D.BullockO. M.CoronelJ. C.BondR. M.PoulsenS. (2022). Predicting vote choice and election outcomes from ballot wording: The role of processing fluency in low information direct democracy elections. Political Communication, 39(5), 652–673.ea
42.
StajkovicA.LuthansF. (1998). Self-efficacy and work-related performance: A meta-analysis. Psychological Bulletin, 124, 240–261. https://doi.org/10.1037/0033-2909.124.2.240.
43.
StasserG.TitusW. (1985). Pooling of unshared information in group decision making: Biased information sampling during discussion. Journal of Personality and Social Psychology, 48, 1467–1478.
44.
van KnippenbergD. (2017). Team innovation. Annual Review of Organizational Psychology and Organizational Behavior, 4(1), 211–233.
45.
van KnippenbergD.De DreuC. K.HomanA. C. (2004). Work group diversity and group performance: An integrative model and research agenda. Journal of Applied Psychology, 89(6), 1008–1022.
46.
WengerE. (1998). Communities of practice: Learning, meaning, and identity. Cambridge University Press.
47.
WickensC.BrauneR.StokesA. (1987). Age differences in the speed and capacity of information processing: 1. A dual-task approach. Psychology and Aging, 2(1), 70–78. https://doi.org/10.1037/0882-7974.2.1.70
