Heard But Not Understood: Language Style Matching As a Predictor of Sentinel Events Among Nursing Staff

Purpose: Communication plays a significant role in maintaining the daily workflow and safety of patients in a healthcare setting. In recent years, there has been increased interest in understanding how communication can affect sentinel events, adverse events, and near misses in a hospital setting. Previous studies have shown that a significant percentage of adverse events were precipitated as a result of communication failures during hall handovers at shift changes and during patient transfers. Therefore, effective communication is necessary to avoid unintentional harm to patients in a healthcare setting. This study examines language style matching (LSM), the action of matching another person's speech pattern based on nine sets of function words, in writing or conversation, between active nurses and nurse residents to evaluate whether teams with a high level of LSM will be associated with fewer sentinel events, near misses, and adverse events compared with teams with lower language style matching. Past studies have examined LSM in romantic relationships as well as corporate environments (Gonzales et al., 2010; Ireland et al., 2011; Tausczik & Pennebaker, 2010), however, this is the first study relating to nursing teams. Methods: Trained researchers administered a survey consisting of basic demographic information, list of closest coworkers, and self-reporting of adverse events. The survey also included a writing prompt (adapted from Pennebacker (2012)) ""Since time immemorial, laymen have doggedly adhered to pearls of folk wisdom such as, "Birds of a feather flock together" or "opposites attract." These platitudes are unquestionably simplistic. Nevertheless, one of the two is bound to be a close approximation of the truth. Which phrase do you believe is more accurate and why? Please spend about 5 minutes on your response.". Then, after data collection, utilizing named coworkers, 58 pairs were formed and LSM and self-reported adverse event data were analyzed using LIWC software. Results: Two logistic regression analyses were conducted. Repeat data was controlled in the first step of the model. Results showed a negative trend between LSM and near misses such that higher LSM was associated with a reduced likelihood of a near miss , b = -30.37 (S.E. = 23.72, Wald χ2 = 1.64, p = .20, odds ratio < .01, 95% C.I. = .001, 10069714.4. Furthermore, a significant positive trend was observed between LSM and sentinel events such that lower LSM was associated with a reduced likelihood of a sentinel event b = 9.27 (S.E. = 7.06), Wald χ2 = 1.73, p = .19, odds ratio < .10577.39, 95% C.I. = .01, 10711997526.96. Conclusions: Due to the reduced likelihood of near misses associated with higher LSM between individuals, further study is warranted. It is likely that the observed positive relationship between LSM and sentinel events is an artifact of data due to the small sample size. However, this research is applicable as a potential screening tool for team curation in a healthcare setting in order to reduce the overall number of near misses in patient-care.